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How is newtsim different from standard CFD or simulation software?

Standard simulation tools use empirical models at a single scale. newtsim runs the full physics chain from quantum mechanics and molecular dynamics through to plant-scale CFD and structural mechanics, GPU-native, with direct data flow between every scale and no third-party solver dependencies. Constitutive behaviour is predicted from first principles rather than empirically fitted.

What does a fixed-price simulation study include?

A newtsim fixed-price study has a defined scope, clear deliverables, fixed cost agreed upfront, and is delivered in weeks rather than quarters. Studies typically include a scoping call, physics-grounded simulation using the appropriate newtsim solvers, results analysis, and a written report with actionable recommendations.

What is physics-grounded simulation?

Physics-grounded simulation derives material properties and constitutive behaviour from lower-scale physics (molecular dynamics and quantum mechanics) rather than from empirical fitting. This gives accurate predictions for novel materials and extreme conditions outside the range of experimental data, and enables root-cause analysis at the mechanistic level.

How does newtsim approach oil and gas flow assurance simulation?

newtsim runs a continuous physics chain from molecular wax crystallisation to full pipeline transient multiphase flow, with no empirical handoffs between scales. Wax appearance temperatures, gel strength, and deposition kinetics are predicted from molecular dynamics (newtsim Bond), passed directly to mesoscale morphology (newtsim Pack), and then propagated into multiphase CFD (newtsim Stream), giving flow assurance predictions that hold outside the range of laboratory data.

Can newtsim simulate battery electrolyte behaviour and degradation?

Yes. The Bond solver runs molecular dynamics for Li-ion transport and solid-electrolyte interphase (SEI) formation; Pack handles electrode morphology at the mesoscale; these results couple upward to cell-scale electrochemical models. This gives physics-grounded predictions of electrolyte degradation, capacity fade, and thermal behaviour without relying solely on empirical ageing fits.

How does physics-grounded drug discovery simulation differ from docking software?

Molecular docking software treats the protein and ligand as rigid bodies and scores binding poses by geometry. Physics-grounded simulation uses molecular dynamics to capture conformational flexibility and explicit solvation effects that rigid-body docking misses, predicting binding free energy, ADMET properties, and metabolic activation from first principles. This is particularly valuable for targets where induced-fit binding or solvent-mediated interactions drive selectivity.

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GPU parallelism maps naturally to the computational kernels underlying molecular dynamics and CFD: large numbers of independent force or flux calculations that can execute simultaneously. newtsim runs all simulation scales GPU-native, avoiding the CPU-to-GPU data transfers that bottleneck traditional solvers which run physics on CPU and only offload selected operations to the GPU. This removes the transfer overhead and allows the full multiscale chain to run without the latency penalties of heterogeneous pipelines.

Does newtsim replace existing simulation tools like ANSYS or COMSOL?

newtsim fills the multiscale gap, connecting molecular-scale physics to the engineering-scale models that tools like ANSYS operate at. It is not a replacement for FEA-only or single-scale workflows where those tools are the right fit. Where newtsim adds value is in problems where constitutive behaviour, material properties, or interfacial physics need to be derived from lower-scale simulation rather than taken from a handbook or empirical fit.

How long does a fixed-price simulation study take?

Most studies complete in 4 to 8 weeks depending on scope. The standard timeline is: scoping call and problem definition in week 1; simulation execution across the relevant physics scales in weeks 2 to 4; results analysis, validation, and report delivery in weeks 5 to 6. More complex multiscale studies with broader operating envelopes may extend to 8 weeks. Scope and timeline are agreed and fixed before work begins.

What deliverables does a simulation study produce?

A newtsim simulation study delivers: a validated multiscale model calibrated to your system; an operating envelope with physics-based safety margins; a written technical report with findings and actionable recommendations; and optionally CFD visualisations or an ML surrogate model (newtsim Neural) for fast design-space exploration by your engineering team.

Does newtsim work for green hydrogen electrolyser and catalyst design?

Yes. The Stream solver handles proton exchange membrane and alkaline electrolyser CFD: multiphase flow, bubble dynamics, and membrane transport. Bond handles catalyst surface reaction molecular dynamics, giving adsorption energies and reaction barriers from first principles rather than from empirical correlations. Neural then produces fast-to-run surrogate models for design-space exploration and stack optimisation, reducing the iteration cost for new catalyst compositions and electrode architectures.

newtsim is a physics-grounded multiscale simulation consulting firm and software platform. We deliver fixed-price simulation studies and platform licences for industrial clients, covering the full physics chain from quantum mechanics and molecular dynamics through to plant-scale CFD and structural mechanics. All solvers run GPU-native.

Does newtsim use artificial intelligence or machine learning?

Yes. newtsim Neural produces ML-trained surrogate models derived from high-fidelity physics simulations. These surrogates run in milliseconds rather than hours, enabling rapid design-space exploration and real-time control without sacrificing physical accuracy. The ML models are trained on physics simulation data, not empirical measurements, so they inherit the accuracy and extrapolation properties of the underlying physics.

How do I get started with newtsim?

Book a free technical scoping call at newtsim.com/demo. Bring a description of your engineering challenge, the physics you think are important, and any data you have. The call is 45 minutes and produces a problem definition, proposed physics chain, and outline scope that forms the basis of a fixed-price proposal.

Can newtsim simulate non-Newtonian fluids?

Yes. newtsim specialises in non-Newtonian flow: yield-stress fluids, viscoelastic materials, shear-thinning and shear-thickening systems, and complex multiphase flows. The Stream solver handles macroscale CFD for these systems; Bond provides the molecular-scale rheology predictions that replace empirical viscosity fits; and the full chain gives accurate behaviour outside the calibrated range of laboratory data.

Does newtsim work for small companies or startups?

Yes. Fixed-price studies are available to clients of any size. The fixed-price, fixed-scope model means you know the cost before committing, making it accessible for smaller organisations without large simulation teams. Many newtsim clients are startups and scale-ups who need physics-grounded analysis early in product development before investing in laboratory or pilot-scale work.

What is the difference between molecular dynamics and CFD?

Molecular dynamics (MD) simulates the motion of individual atoms and molecules to compute material properties such as viscosity, diffusivity, reaction rates, and phase behaviour, from first principles. Computational fluid dynamics (CFD) models bulk fluid flow at the engineering scale using those material properties as inputs. newtsim connects the two: MD provides accurate constitutive inputs that CFD uses for engineering-scale predictions, rather than relying on empirical correlations.

What is a surrogate model in simulation?

A surrogate model (also called a reduced-order model or emulator) is a fast mathematical approximation of a complex simulation. newtsim Neural builds ML surrogates trained on high-fidelity physics simulation data. Once trained, a surrogate evaluates in milliseconds instead of hours, enabling real-time optimisation and design-space exploration. Because surrogates are trained on physics data, they are more accurate than empirical correlations, especially outside the training range.

What deliverables does a newtsim simulation study produce?

A newtsim simulation study delivers: (1) a validated multiscale model calibrated to your system; (2) an operating envelope with physics-based safety margins; (3) a written technical report with findings and actionable recommendations; and optionally (4) CFD visualisations and an ML surrogate model for fast ongoing design-space exploration by your engineering team.

Nuclear Decommissioning

Nuclear Decommissioning · Case Study

Hanford Tank Waste Gas Generation: Radiolysis Kinetics and Thermodynamic Equilibrium Modelling for ILW Package Safety

Executive Summary

Tank 241-SY-101 at the Hanford Site in Washington State is the most extensively documented gas generation hazard in the history of nuclear waste management. Constructed between 1976 and 1976 as one of 28 double-shell tanks at Hanford, SY-101 held approximately 1.1 million gallons of radioactive slurry generated during four decades of weapons-grade plutonium production -- a complex, highly alkaline mixture of nitrate and nitrite salts, organic complexants, and fission products carrying roughly 22 million curies of combined Cs-137 and Sr-90 across the Hanford tank farm complex. By the late 1980s, the tank was exhibiting spontaneous gas release events every 80-110 days, each releasing 3,000-8,000 cubic feet of flammable hydrogen and nitrous oxide into the dome space -- elevating concentrations to near the lower explosive limit of the mixture. These were not theoretical risks. The events occurred on a documented schedule, they were measured, and they remained unresolved for years while engineers debated remediation options. The fundamental problem was that no one had built a predictive model of gas retention and release at design time. The waste chemistry, the bubble dynamics in viscoplastic sludge, the Sudden Gas Release Event mechanism -- all of this was discovered after the fact, by monitoring a tank that was already a hazard. A continuous mixer pump programme eventually suppressed the events between 1993 and 1995. The full remediation of Hanford's 177 tanks -- the largest radioactive liquid waste inventory in the US DOE complex -- remains decades from completion and is subject to continuous cost escalation.

The direct consequence of the gas generation failure at SY-101 was not an explosion. It was the revelation that the entire tank farm's Documented Safety Analysis (DSA) was operating on bounding assumptions that were no longer bounding. Three double-shell tanks flagged in this study show headspace hydrogen at 12,000-38,000 ppm against a 25% LEL operational limit of 10,000 ppm. Engineering controls -- forced ventilation of annulus spaces -- are in place pending DSA revision. Had a mechanistic radiolysis kinetics model been integrated into the original DSA, tracking the 85 relevant chemical species through their 400 reaction pathways, the Sudden Gas Release Event mechanism in viscoplastic sludge would have been predicted rather than discovered. The mixer pump programme would have been part of the original design basis, not an emergency response.

A simulation assessment of this type, applied during the original DSA development or at any major DSA revision cycle, identifies the SGRE trigger threshold for each tank, predicts P90 release volumes and dome concentration exceedance probabilities, and specifies the ventilation interlock setpoints and personnel access controls that prevent a gas release event from becoming a flammability incident. The grouted package analysis -- demonstrating compliance with 10 CFR Part 61 H2 generation limits at 8.75x margin at five years post-pour -- is simultaneously the safety case basis for package acceptance and the calibration dataset for newtsim livesim: the gas generation rate, temperature evolution, and H2 headspace concentration within grouted packages define the sensor array for real-time monitoring, replacing periodic package surveys with continuous automated assurance that catches any deviation from predicted performance within minutes rather than months.

Scenario Background

The scenario involves a prime contractor managing remediation of a tank farm complex analogous to Hanford. The waste inventory -- generated from 1944 to 1988 during weapons-grade plutonium production for the US nuclear weapons programme -- is stored in two tank generations.

The single-shell tanks (SSTs) comprise 149 units of carbon steel construction dating from 1944 to 1964. Their nominal capacity ranges from 500,000 to 1,000,000 gallons each, and many have confirmed or suspected structural leaks into the surrounding vadose zone. The waste form is primarily dried saltcake and settled sludge with residual liquor in some tanks, totalling approximately 34 million gallons across the SST fleet.

The double-shell tanks (DSTs) comprise 28 units dating from 1968 to 1986, each with a primary vessel plus continuously monitored annular containment space. Their nominal capacity ranges from 1,000,000 to 1,160,000 gallons, and the waste forms include supernatant liquor, saltcake, and settled sludge, totalling approximately 22 million gallons.

Total tank waste radionuclide inventory (as of 2020):

Radionuclide	t(1/2)	Estimated Total Activity	Primary Waste Phase
Cs-137	30.2 yr	~70-90 MCi	Dissolved in supernatant; partially sorbed to sludge
Sr-90	28.8 yr	~300-350 MCi	Sludge-associated (strontianite/sorbate)
Tc-99	213,000 yr	~0.02 MCi	Dissolved (pertechnetate TcO4-)
Pu-239/240	24,100/6,563 yr	~0.5 MCi	Sludge
Am-241	432 yr	~0.3 MCi	Sludge
Gross beta-gamma	—	~1,100 MCi (total site)	Mixed

Three DSTs were flagged for elevated annulus hydrogen. The SY-101 analog tank, at pH 13.2 with 8.4 M NaNO3, 3.1 M NaNO2, and 12.3 g/L organic TOC at a dose rate of 18 Gy/hr, showed annulus H2 of 38,000 ppm (3.8% v/v). The AN-105 analog at pH 12.8 with 6.7 M NaNO3, 2.2 M NaNO2, and 6.8 g/L organic TOC at 11 Gy/hr showed 24,000 ppm (2.4% v/v). The AW-101 analog at pH 13.5 with 11.2 M NaNO3, 1.8 M NaNO2, and 4.1 g/L organic TOC at 9 Gy/hr showed 12,000 ppm (1.2% v/v). All three tanks exceed the DSA operational limit of 10,000 ppm (1% v/v), and interim engineering controls (continuous forced ventilation of annulus space) are in place pending DSA revision.

SY-101 analog tank sludge characterisation (core sample data):

Radionuclide	Activity (Bq/L sludge)	Activity (Ci/L)	Phase
Cs-137	3.4 x 10¹²	92	Dissolved supernatant + sorbed
Sr-90	1.8 x 10¹²	49	Sludge-sorbed
Pu-239	2.2 x 10⁹	0.059	Sludge particle
Am-241	1.4 x 10⁹	0.038	Sludge particle
Tc-99	8.1 x 10⁷	0.0022	Dissolved
Total beta-gamma dose rate (sludge layer)	18 Gy/hr	—	Cs-137 + Sr-90 dominant

The Challenge

Gas generation in Hanford tank waste is a multi-pathway process in a highly alkaline, high-ionic-strength, high-radiation-field environment unlike any encountered elsewhere in the industrial chemistry literature.

The first and most significant mechanism is gamma and beta radiolysis of water, producing H2, O2, H2O2, OH radicals, and aqueous electrons. The rate is governed by absorbed dose rate and G-values modified by ionic strength and organic content. In high-nitrate solutions (8-11 M NaNO3), ionic strength substantially suppresses H2 G-values relative to pure water: G(H2) decreases from 0.048 mol/100 J in pure water to 0.032 mol/100 J at 8 M NaNO3 due to salt-enhanced radical recombination.

The second mechanism is nitrate/nitrite thermal reduction, which becomes Arrhenius-activated above approximately 60°C. This pathway produces N2 and N2O from NO3-/NO2- and is significant in hotter tanks and in grouted packages with elevated decay heat. Importantly, N2O has a lower explosive limit of 2.9% v/v -- lower than H2 at 4% v/v -- so the mixture LEL is approximately additive, reducing the effective LEL to about 3.5% v/v for the H2/N2O/N2 mixture found in tank headspaces.

The third mechanism is organic complexant oxidative decomposition. EDTA, citrate, and HEDTA at 0.01-0.3 M undergo radiolytic and thermal oxidation, producing CO2, H2, and low-molecular-weight organic fragments. This pathway is both a gas source and a complexant destruction pathway that can release actinides from chelate complexes. At the SY-101 analog TOC of 12.3 g/L, this pathway contributes approximately 22% of total H2 generation.

The fourth mechanism is residual alpha radiolysis from actinide alpha decay. G(H2) for alpha particles is approximately 0.110 mol/100 J -- more than 3x the gamma value -- due to high local ionisation density in the alpha particle track. However, alpha ranges in sludge are only about 30 um, confining this pathway to near-actinide-particle regions and contributing approximately 4-8% of total H2 at the Hanford waste compositions studied.

Beyond the generation mechanisms, retained gas and SGRE dynamics present a distinct challenge. In viscoplastic waste sludge (yield stress 1-200 Pa, viscosity 10-500 mPa.s), gas bubbles cannot escape freely. The retained gas fraction (RGF) builds until a buoyant instability threshold (RGF*) is reached, at which point a fraction of retained gas releases in a Sudden Gas Release Event over minutes to hours. The SY-101 tank was the most dramatic historical example: by the late 1980s, events were releasing 3,000-8,000 ft³ of H2/N2O gas per event approximately every 80-110 days, elevating dome-space gas concentrations to near-flammable levels. A continuous mixer pump programme (1993-1995) suppressed episodic events by homogenising the waste and preventing the crust formation that acted as a gas trap.

After vitrification or grouting and placement into interim storage packages, residual gas generation persists from radiolysis within the grout pore water and decay of long-lived radionuclides. The 10 CFR Part 61 acceptance criterion limits H2 generation from grouted LLW/ILW packages to 3.5 cm³/kg/hr, and package pressure must remain below structural limits over a 300-year disposal timescale. Cs-137 and Sr-90 decay heat creates internal temperature gradients within grouted packages, with package centre temperatures up to 74°C above ambient at the pour stage -- significantly above the 40°C assumed in conservative package acceptance calculations -- and temperature has a strong Arrhenius effect on gas generation kinetics.

Real-World Basis and Reference Data

This study is grounded in the most extensively documented tank waste gas generation dataset in the DOE complex: the SY-101 tank remediation programme (1993-2000), which produced an unparalleled empirical dataset for tank waste radiolysis modelling.

SY-101 began exhibiting periodic spontaneous gas release events in 1978. By the late 1980s, events were releasing 3,000-8,000 ft³ of flammable H2/N2O gas mixture per event approximately every 80-110 days. The tank held approximately 1.1 million gallons of radioactive slurry with a complex non-Newtonian crust-slurry-sludge layer structure. From 1993, a mixer pump operated continuously to homogenise the waste, reducing SGRE frequency and eventually suppressing events by 1995. Between 2000 and 2004, dilution and pump operations reclassified tank contents from liquid supernatant to saltcake, eliminating further SGRE risk. SY-101 remains the definitive case study in tank waste gas management.

The model draws on the full PNNL radiolysis research programme: measured H2 and N2O generation rates during SY-101 mixer pump operation (1993-1997), gas retention and buoyant displacement measurements, and systematic G-value characterisation across ionic strengths from 2-10 M NaNO3 yielding G(H2) = 0.032-0.058 mol/100 J for gamma radiolysis. Independent validation data comes from Savannah River Site Tank 50H gas generation measurements at lower ionic strength (5-6 M NaNO3), UK grouted ILW package gas generation studies reporting effective diffusivity values of De(H2) = 2.1-4.8 x 10⁻¹¹ m²/s in OPC-based grouts, and IAEA G-value correlations for radiolytic H2 in aqueous ILW. The regulatory framework follows NRC grouted package acceptance criteria (3.5 cm³/kg/hr H2 limit) and DOE Documented Safety Analysis methodology.

Simulation Methodology

The simulation pipeline integrates a mechanistic radiolysis kinetics model, thermodynamic gas equilibrium and bubble dynamics model, stochastic SGRE model, and finite-element package thermal analysis, with each stage consuming outputs from the preceding stage.

Radiolysis kinetics model

The mechanistic chemical kinetics model was implemented using the FACSIMILE/CHEMSIMUL framework, adapted for nuclear waste chemistry. The model tracks 85 chemical species through approximately 400 reaction pathways covering initiation, propagation, termination, and radical recombination. Key species include H2O, OH radical, H radical, solvated electron (e-aq), H2O2, H2, O2, NO3-, NO2-, N2O, N2, NH3, HNO3, and organic complexant fragments (acetate, formate, oxalate, and EDTA fragments as lumped parameters).

G-values are parameterised per radiation type and waste chemistry from the PNNL radiolysis measurement programme:

Radiation Type	G(H2) (mol/100 J)	G(N2O) (mol/100 J)	G(H2O2) (mol/100 J)	G(O2) (mol/100 J)
Gamma/beta (pure water, 0 M salt)	0.048	—	0.073	0.026
Gamma/beta (8 M NaNO3, no organics)	0.032	0.025	0.041	0.018
Gamma/beta (8 M NaNO3 + 12 g/L TOC organics)	0.058	0.031	0.052	0.022
Alpha (high LET, pure water)	0.110	—	0.125	0.015
Alpha (high LET, high nitrate)	0.095	0.012	0.108	0.011

The enhancement of G(H2) in the presence of organics (0.032 to 0.058 mol/100 J) reflects organic radical decomposition contributing to molecular H2 production -- the EDTA and HEDTA oxidation pathway that is particularly important in the SY-101 analog tank with TOC = 12.3 g/L.

Temperature dependence follows an Arrhenius form, k(T) = k25 x exp[-Ea/R x (1/T - 1/298.15)], with Ea values fitted to Hanford programme data. The thermal decomposition of nitrate and nitrite is strongly temperature-sensitive above 60°C, with activation energies of 85 kJ/mol for NO3- and 62 kJ/mol for NO2-.

Spatial resolution uses a 1D column model through waste depth (supernatant, saltcake, sludge layers), coupled to a 2D axisymmetric thermal model of the tank interior. Layer thicknesses and compositions derive from core sample characterisation data.

Thermodynamic equilibrium and bubble dynamics

Gas solubility in high-ionic-strength waste follows Henry's Law coefficients modified using the Sechenov salt-out correction for H2 and N2O in concentrated NaNO3/NaNO2 solutions. At 8 M NaNO3, H2 solubility is reduced by a factor of approximately 1.8 relative to pure water, increasing bubble nucleation tendency and reducing the dissolved gas inventory in the liquid phase.

The retained gas fraction is calculated using a population balance model. Nucleation is heterogeneous, occurring at waste particle surfaces, and is suppressed by the Jones-Ray effect at high ionic strength; the nucleation rate follows J = A x exp(-ΔG*/kT) with ΔG* modified for a surface contact angle in sludge of approximately 35 degrees. Bubble growth is limited by diffusion through high-viscosity waste, with Stokes-Einstein diffusivity corrections applied for viscoplastic media using a modified Wilke-Chang correlation: D_eff = D_water x (eta_water/eta_waste)⁰.⁶.

The buoyant instability threshold follows the established buoyant displacement criterion, RGF* = tau_y / (Delta_rho x g x H_waste), where tau_y is yield stress, Delta_rho is the gas-waste density difference, g = 9.81 m/s², and H_waste is the waste column depth. For the SY-101 analog this gives RGF* = 28-34% v/v, with the range reflecting yield stress uncertainty of +/-40%.

Stochastic SGRE model

SGREs are triggered when the spatially-averaged RGF exceeds RGF* in any tank layer. The gas release fraction per event is log-normally distributed with a geometric mean of 0.35 and a scale parameter of 0.15 on the log scale, fitted to the SY-101 SGRE event history. Gas composition at release is H2 at 40-65%, N2O at 20-35%, and N2 as the balance, calculated from the equilibrium model at release conditions. Each tank configuration is evaluated over 1,000 Monte Carlo realisations, producing event frequency, release volume, peak dome H2 concentration, time above LEL, and time above the 25% LEL operational limit.

ILW package thermal-gas analysis

FEM thermal analysis of grouted ILW packages (1.2 m x 1.2 m x 1.8 m stainless-steel box, 800K elements) models grout composed of OPC:PFA:BFS at a 25:50:25 mass ratio with thermal conductivity of 0.8-1.2 W/m.K (temperature-dependent) and a water-to-cement ratio of 0.45. The decay heat input is time-varying, dominated by Cs-137 and Sr-90, modelled as a declining exponential over the 300-year simulation period.

Gas generation within the grout matrix uses reduced G-values reflecting radiation attenuation in the dense grout (attenuation coefficient for Cs-137 gamma in OPC grout: mu = 0.23 cm⁻¹) and reduced free water availability (G_eff = G_0 x w/c x 0.82). H2 diffusion through the grout uses De = 3 x 10⁻¹¹ m²/s (OPC:PFA:BFS median value from UK grouted ILW experimental data), with pore pressure calculated from the ideal gas law for H2 in the grout pore volume. The 300-year transient uses accelerated time-stepping: 1 day for the first year, 1 month for years 1-50, and 6 months for years 50-300.

Simulation Caveats

G-value universality. The G-values used in this model were measured on Hanford-specific waste simulants at ionic strengths from 2-10 M. Extrapolation to the exact chemistry of the three flagged tanks involves interpolation across a multidimensional parameter space (pH, ionic strength, organic content, temperature, dose rate). Uncertainty estimated at +/-25% on the gas generation rate.
Rheology and RGF uncertainty.* Waste rheology (yield stress and viscosity) is highly sensitive to temperature, shear history, and dissolved species concentration. RGF* is proportional to yield stress; uncertainty in yield stress (+/-40% based on replicate rheometer measurements on core samples) translates to +/-40% uncertainty in RGF* and hence SGRE trigger timing. The Monte Carlo SGRE model propagates this uncertainty through the event release distribution.
Organic complexant decomposition. The lumped-parameter treatment of EDTA, HEDTA, and citrate organic chemistry introduces model error at the +/-30% level for the organic decomposition H2 pathway. For the SY-101 analog tank (TOC = 12.3 g/L), this pathway contributes approximately 22% of total H2 generation. High-fidelity EDTA/HEDTA decomposition kinetics is identified as a model refinement priority for DSA revision.
Grout long-term performance extrapolation. The 300-year pore pressure prediction extrapolates cement mineralogy and diffusivity data well beyond validated timescales. Portlandite carbonation and C-S-H gel structural evolution at century timescales are not captured. Flagged in the DSA as a research gap requiring confirmation from long-term analogue studies (Roman concrete, natural cement analogues).
Temperature spike at pour. The initial package temperature spike to 56°C at pour is driven by combined exothermic cement hydration and radioactive decay heat. The cement hydration contribution (peak 12-72 hours) carries +/-15°C uncertainty from grout formulation variability. This drives the highest gas generation rate in the package life and the approach to the 10 CFR Part 61 limit at pour.
SGRE gas composition uncertainty. The H2/N2O/N2 release composition is calculated from the equilibrium model at release conditions. The N2O content is particularly sensitive to nitrite concentration and temperature; uncertainty in N2O fraction (+/-30%) affects the mixture LEL calculation and the time-above-LEL prediction.

Key Predictions and Results

Tank gas generation and SGRE characterisation:

Parameter	SY-101 Analog	AN-105 Analog	AW-101 Analog	Units
Baseline H2 generation rate	0.18	0.12	0.09	mol/hr/m³ sludge
N2O generation rate	0.07	0.041	0.028	mol/hr/m³ sludge
N2 generation rate	0.031	0.019	0.013	mol/hr/m³ sludge
CO2 generation rate (from organic decomposition)	0.024	0.010	0.006	mol/hr/m³ sludge
Alpha radiolysis contribution to H2	6%	5%	4%	% of total H2
Organic decomposition contribution to H2	22%	14%	9%	% of total H2
RGF at instability threshold (RGF*)	28-34%	22-29%	18-25%	v/v
Waste rheological yield stress	65-140 Pa	38-82 Pa	22-54 Pa	Pa (range = temp. variation)
SGRE release volume (P50 event)	3,800	2,100	1,200	ft³ equivalent
SGRE release volume (P90 event)	5,200	3,100	1,900	ft³ equivalent
Inter-SGRE period (median)	13	22	38	months
Peak dome H2 concentration post-SGRE (P50 event)	3.1%	2.2%	1.6%	v/v
H2 LEL reached?	Yes (4% v/v) -- near	No	No	—
Time above 25% LEL (P90 event, continuous ventilation)	47	0	0	minutes
Required dome ventilation rate to maintain <25% LEL	18,000	7,400	3,200	m³/hr

Hanford Tank Waste Gas Generation Rate by Tank

Hanford Tank SGRE Peak Dome H2 vs LEL

The SY-101 analog presents the most significant SGRE risk. P90 events release 5,200 ft³ of gas mixture, elevating dome H2 to 3.1% v/v -- 78% of the H2 LEL. With simultaneous N2O contribution (estimated 0.8-1.2% v/v), the composite mixture LEL of approximately 3.5% v/v is approached within the uncertainty range. The DSA must be revised to acknowledge this residual flammability risk and require continuous dome-space H2 monitoring at 5-minute intervals, forced dome ventilation maintaining a minimum of 18,000 m³/hr, and a hard interlock on all personnel access at greater than 50% composite LEL.

Grouted ILW package performance (SY-101 analog waste, OPC:PFA:BFS grout, 25:50:25 ratio):

Parameter	t=0 (at pour)	t=5 yr	t=50 yr	t=150 yr	t=300 yr	10 CFR Part 61 Limit
H2 generation rate (cm³/kg/hr)	2.8	0.40	0.18	0.08	0.04	3.5
Margin to 10 CFR Part 61 limit	20%	8.75x	19.4x	43.8x	87.5x	—
Peak internal temperature (°C, above 25°C ambient)	56	74	48	31	20	—
Pore pressure (MPa, steady-state)	0.02	0.08	0.14	0.18	0.21	<40 MPa (grout)
H2 in headspace (% v/v, steady-state closed package)	1.8	2.1	0.9	0.3	0.2	<4% v/v (LEL)
Package structural integrity	Confirmed	Confirmed	Confirmed	Confirmed	Confirmed	—

Hanford ILW Package H2 Generation Over 300 Years

The initial H2 generation rate at pour (2.8 cm³/kg/hr) approaches but remains below the 3.5 cm³/kg/hr 10 CFR Part 61 limit. The rate is highest at pour due to the combination of maximum radionuclide activity and elevated pore water temperature from cement hydration plus decay heat, producing a peak of 56°C. The rate declines monotonically thereafter, reaching 0.4 cm³/kg/hr at 5 years as Cs-137/Sr-90 dose rate decays and the cement matrix matures.

The peak pore pressure of 0.21 MPa at 300 years is well within both the grout compressive strength limit (40 MPa, by a factor of 190x) and the package weld integrity limit (2.8 MPa design burst pressure, by a factor of 13x). H2 diffusion through the grout at De = 3 x 10⁻¹¹ m²/s limits pressure build-up effectively; the headspace H2 concentration peaks at 2.1% v/v at 5 years then declines as the gas generation rate falls below the diffusive release rate.

Gas generation sensitivity analysis (one-at-a-time, +/-1 sigma uncertainty):

Parameter	Effect on H2 Rate	Dominant Stage
G(H2) gamma value (+/-20%)	+/-18% H2 rate	All stages
Grout water-to-cement ratio (+/-0.05)	+/-12% H2 rate	Post-pour (first 50 yr)
Package temperature (+/-8°C at peak)	+/-25% thermal decomposition rate	Years 5-50
Organic TOC content in waste (+/-30%)	+/-22% H2 rate	First 10 years
Grout De for H2 (+/-50%)	+/-8% headspace concentration	Years 1-100
Alpha radiolysis G-value (+/-30%)	+/-2% total H2 rate	All stages (minor pathway)

Temperature is the dominant uncertainty driver for the nitrate/nitrite thermal decomposition pathway during years 5-50 when package temperatures are elevated. G-value uncertainty is the dominant factor at all other stages.

Validation and Comparison Methodology

Primary validation dataset -- SY-101 operational measurements:

Gas generation rates measured during SY-101 mixer pump operation from 1993 to 1997 provide the calibration dataset. The model was compared against measured H2 and N2O generation rates as a function of temperature and mixing intensity at known waste chemistry and activity levels.

Comparison Point	Measured	Model Prediction	Discrepancy
H2 rate at 40°C, no mixing	0.14 mol/hr/m³	0.13 mol/hr/m³	-7%
H2 rate at 55°C, continuous mixing	0.31 mol/hr/m³	0.28 mol/hr/m³	-10%
N2O rate at 40°C, no mixing	0.055 mol/hr/m³	0.062 mol/hr/m³	+13%
N2O rate at 55°C	0.11 mol/hr/m³	0.098 mol/hr/m³	-11%
H2 generation rate (full temperature range, all mixing states)	Published range	Model range	Within +/-18% at all data points

The validation target was model H2 generation rate within +/-25% of SY-101 measurements across the temperature range 25-80°C. The study achieved +/-18% across all data points.

Secondary validation -- Savannah River Site analogue:

H2 and N2O generation data from SRS Tank 50H waste -- chemically similar at lower ionic strength (5-6 M NaNO3) -- were used as an independent check. Model predictions at SRS-equivalent chemistry fell within +/-22% of published measurements.

Package model validation -- UK grouted ILW programme:

UK experimental programmes measured H2 and CO2 release rates from grouted ILW simulant packages using OPC:PFA:BFS grout at similar water-to-cement ratios. Measured De values (De(H2) = 2.1-4.8 x 10⁻¹¹ m²/s) are consistent with the model input (De = 3 x 10⁻¹¹ m²/s median). Predicted package H2 release rates reproduce experimental measurements within +/-30%.

Regulatory cross-check -- NRC grouted package acceptance criteria:

NRC H2 generation limits for grouted LLW/ILW packages served as the primary acceptance benchmark. The model predicts compliance at t=0 (pour) with 20% margin, and compliance at t=5 yr with 8.75x margin, both satisfying the regulatory requirement.

Deliverables

Radiolysis Kinetics Model -- fully documented, validated kinetics model (FACSIMILE source code and all G-value datasets) for the relevant waste compositions; structured for transfer to the operator's in-house safety analysis team for future DSA revisions; includes G-value interpolation routines for arbitrary chemistry conditions
SGRE Risk Assessment -- Monte Carlo SGRE characterisation for three flagged tanks; event frequency, magnitude, and flammability hazard distributions; P50/P90 release volume and dome concentration estimates; recommended dome-space monitoring setpoints, ventilation interlock specifications, and personnel access control procedures; direct input to DSA revision
ILW Package Gas Generation Report -- thermal-gas analysis for grouted package configurations at three tank compositions; 10 CFR Part 61 compliance demonstration at all time points; sensitivity analysis on grout formulation (OPC:PFA:BFS ratio, water-to-cement ratio, admixture type); recommended minimum cooling period before grouting for each tank waste type
Long-Term Gas Pressure Analysis -- 300-year pore pressure evolution; structural integrity confirmation relative to grout compressive strength and package weld burst pressure; identification of grout property uncertainties requiring long-term monitoring programme; recommended inspection intervals for storage facility
Acceptance Criteria Derivation -- recommended maximum waste loading per package, minimum grout-to-waste ratio, cooling period before grouting, and maximum package temperature at pour; technical basis for package specification revision
All Simulation Files -- FACSIMILE input files (kinetics model), FEM newtsim Span archive (package thermal model), Python post-processing scripts, SGRE Monte Carlo code; formatted for NRC independent review and DOE Office of River Protection (ORP) technical review board

Delivery timeline: 9 weeks from receipt of waste characterisation data (core sample analyses), rheology measurements (yield stress and viscosity vs. temperature), and radionuclide inventory files.

This case study is an illustrative reference scenario demonstrating newtsim's simulation methodology. All company names, personnel, and specific operational data are fictional. The incident descriptions draw on publicly documented real-world events cited in the frontmatter.