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DOE OSTI2026

The Role of Nuclear Data Sensitivities in Prompt α-Eigenvalue Predictions of Delayed Critical Benchmarks

Alpha (α) eigenvalues, which describe the logarithmic time derivative of the neutron population in a multiplying system, are integral to time-dependent behavior and diagnostic applications. However, uncertainties in the evaluated nuclear data can significantly impact the accuracy of transport simulations for such quantities. This work explores the use of machine learning models to predict two key outputs, α-eigenvalues and keff bias, using input features derived from α-eigenvalue sensitivities to nuclear data. The criticality safety benchmark models used in this study come from the International Handbook of Evaluated Criticality Safety Benchmark Experiments. Three models, random forest, XGBoost, and NGBoost, are trained on both energy-resolved and energy-summed α sensitivities. For the α-eigenvalue bias prediction, NGBoost achieved the highest R 2 (0.9476) using energy-resolved features, while XGBoost performed best using summed sensitivities. In contrast, when predicting the keff bias, all the models showed moderate predictive capability (best R 2 ≈ 0.72), as the mapping from the static α-sensitivities to the static keff bias was less direct. SHAP (SHapley Additive exPlanations) analysis was used to interpret the model predictions. Across both prediction tasks, the features associated with neutron capture [H-1 (n, γ)], uranium scattering reactions (such as 235 U elastic/inelastic), and actinide capture/fission reactions (such as 239 Pu and 234 U) were consistently identified as the most impactful. This highlights the key role of specific nuclear reactions and energy ranges in shaping both time-dependent and steady-state criticality behavior. These results demonstrated that α-sensitivities, despite being computed for time-dependent metrics, can provide valuable insights for predicting both α-eigenvalues and the keff bias. Moreover, machine learning models offer a promising pathway for uncovering important nuclear data dependencies and guiding future data evaluation efforts.

Nuclear data↗

NASA NTRS2005

V and V of ISHM Software for Space Exploration

NASA has established a far-reaching and long-term program for robotic and manned exploration of the solar system, beginning with missions to the moon and Mars. The Crew Transportation System (CTS), a key system for space exploration, imposes four requirements' that ISHM addresses. These requirements have a wide range of implications for V&V and certification of ISHM. There is a range of time-criticality for ISHM actions, from prognostication, which is often (but not always) non-time-critical, to time-critical state estimation and system management under off-nominal emergency conditions. These are externally imposed requirements on ISHM that are subject to V&V. - In addition, a range of techniques are needed to implement an ISHM. The approaches to ISHM are described elsewhere. These approaches range from well-understood algorithms for low-level data analysis, validation and reporting, to AI techniques for state estimation and planning. The range of techniques, and specifically the use of AI techniques such as reasoning under uncertainty and mission planning (and re-planning), implies that several V&V approaches may be required. Depending on the ISHM architecture, traditional testing approaches may be adequate for some ISHM functionality. The AI-based approaches to reasoning under uncertainty, model-based reasoning, and planning share characteristics typical of other complex software systems, but they also have characteristics that set them apart and challenge standard V&V techniques. The range of possible solutions to the overall ISHM problem impose internal challenges to V&V. The V&V challenges increase when hard real-time constraints are imposed for time-critical functionality. For example, there is an external requirement that impending catastrophic failure of the Launch Vehicle (LV) at launch time be detected and life-saving action be taken within two seconds. In this paper we outline the challenges for ISHM V&V, existing approaches and analogs in other software application areas, and possible new approaches to the V&V challenges for space exploration ISHM.

Markosian, Lawrence↗

NASA NTRS1995

Effect of turbulence models on criticality conditions in swirling flows

The critical state of vortex cores downstream of vortex breakdown has been studied. Base vortical flows were computed using the Reynolds-averaged, axisymmetric Navier-Stokes equations. Standard K - epsilon, RNG and second-order Reynolds stress models were employed. Results indicate that the return to supercriticality is highly dependent on the turbulence model. The K - epsilon model predicted a rapid return of the vortex to supercritical conditions, the location of which showed little sensitivity to changes in the swirl ratio. The Reynolds stress model predicted that the vortex remains subcritical to the end of the domain for each of the swirl ratios employed, and provided results in qualitative agreement with experimental work. The RNG model produced intermediate results, with a downstream movement in the critical location with increasing swirl. Calculations for which area reductions were introduced at the exit in a subcritical flow were also performed using the Reynolds stress model. The structure of the resulting recirculation zone was altered significantly. However, when area reductions were employed within supercritical flows as predicted using the two-equation models, no significant influence on the recirculation zone was noted.

Gatski, Thomas B.↗

DOE OSTI2023

Assessing continuum plasticity postulates with grain stress and local strain measurements in triaxially compressed sand

Critical state and continuum plasticity theories have been used in research and engineering practice in soil and rock mechanics for decades. These theories rely on postulated relationships between material stresses and strains. Some classical postulates include coaxiality between stress and strain rates, stress–dilatancy relationships, and kinematic assumptions in shear bands. Although numerical and experimental data have quantified the strains and grain kinematics in such experiments, little data quantifying grain stresses are available. Here, we report the first-known grain stress and local strain measurements in triaxial compression tests on synthetic quartz sands using synchrotron X-ray tomography and 3D X-ray diffraction. We use these data to examine the micromechanics of shear banding, with a focus on coaxiality, stress-dilatancy, and kinematics within bands. Our results indicate the following: 1) elevated deviatoric stress, strain, and stress ratios in shear bands throughout experiments; 2) coaxial principal compressive stresses and strains throughout samples; 3) significant contraction along shear bands; 4) vanishing volumetric strain but nonvanishing stress fluctuations throughout samples at all stages of deformation. Our results provide some of the first-known in situ stress and strain measurements able to aid in critically evaluating postulates employed in continuum plasticity and strain localization theories for sands.

42 ENGINEERING↗

DOE OSTI2023

Mapping out the thermodynamic stability of a QCD equation of state with a critical point using active learning

The Beam Energy Scan Theory (BEST) collaboration's equation of state (EoS) incorporates a three-dimensional Ising model critical point into the quantum chromodynamics (QCD) equation of state from lattice simulations. Furthermore, it contains four free parameters related to the size and location of the critical region in the QCD phase diagram. Certain combinations of the free parameters lead to acausal or unstable realizations of the EoS that should not be considered. In this work, we use an active learning framework to rule out pathological EoS efficiently. We find that checking stability and causality for a small portion of the parameters' range is sufficient to construct algorithms that perform with > 96 % accuracy across the entire parameter space. Though in this work we focus on a specific case, our approach can be generalized to any EoS containing a parameter space-class correspondence.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Catalytic Bias in Enzymatic Metal Cofactor-Based Oxidation-Reduction Catalysis

Catalytic bias refers to the relative rate preference of a catalyst for either the forward or reverse direction. In enzymatic metal cofactor-based oxidation-reduction catalysis, the tuning of catalytic bias plays an underlying role in controlling rates of reactivity. For this, enzymes have evolved complex active sites that can exist in multiple oxidation states with differing reduction potentials in order to achieve challenging multi-step, oxidation-reduction reactions. Conceivably, the relative stability of the intermediates that contribute to determining the rate-limiting step of the catalytic cycle could impose catalytic bias, although mechanisms for this concept are just beginning to be realized. As one example, recent work on Clostridium pasteurianum [FeFe]-hydrogenases which catalyze reversible hydrogen oxidation have shown that the differential stabilization/destabilization of active site oxidation states through either static or dynamic protein interactions can preferentially promote either the hydrogen oxidation or proton reduction direction of the reaction. This revealed how an enzymatic cofactor can impose bias in oxidation-reduction catalysis through various tuning mechanisms by protein scaffold interactions. The hypothesis based on achieving catalytic bias through the modulation of cofactor oxidation states critical for the reaction cycle can be extended more generally to other cofactor-based oxidation-reductions catalysts. The current understanding of catalytic bias has significant implications for the design of synthetic catalysts used in industrial settings, as well as providing a greater fundamental understanding of the factors that control metabolic processes in all life.

catalysis↗

DOE OSTI2023

Synergizing a Large Ordinary Nernst Effect and Axis‐Dependent Conduction Polarity in Flat Band KMgBi Crystals

The exploration of quantum materials in which an applied thermo/electrical/magnetic field along one crystallographic direction produces an anisotropic response has led to unique functionalities. Along these lines, KMgBi is a layered, narrow gap semiconductor near a critical state between multiple Dirac phases due to the presence of a flat band near the Fermi level. The valence band is highly anisotropic with minimal cross-plane dispersion, which, in combination with an isotropic conduction band, enables axis-dependent conduction polarity. Thermopower and Hall measurements indicate dominant p-type conduction along the cross-plane direction, and n-type conduction along the in-plane direction, leading to a significant zero-field transverse thermoelectric response when the heat flux is at an angle to the principal crystallographic directions. Additionally, a large Ordinary Nernst effect (ONE) is observed with an applied field. It arises from the ambipolar term in the Nernst effect, whereby the Lorentz force on electrons and holes makes them drift in opposite directions so that the resulting Nernst voltage becomes a function of the difference between their partial thermopowers, greatly enhancing the ONE. It is proven that axis-dependent polarity can synergistically enhance the ONE, in addition to leading to a zero-field transverse thermoelectric performance.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Strong pinning and slow flux creep relaxation in Co-doped CaFe 2 As 2 single crystals

In this paper we report on measurements of critical current densities J c and flux creep rates S of freestanding Ca(Fe 1–x Co x ) 2 As 2 (x ≈ 0.033) single crystals with T c ≈ 15.7 K by performing magnetization measurements. The magnetic field dependences of J c at low temperature display features related to strong pinning. In addition, we find that the system displays small flux creep rates. The characteristic glassy exponent, μ, and the pinning energy, U 0 , display exceptional high values for pristine crystals. We find that for magnetic fields between 0.3 T and 1 T, μ decreases from ≈ 2.8 to ≈ 2 and U 0 remains ≈ 300 K. Analysis of the pinning force indicates that the mechanism is similar to the observed in polycrystalline systems in which grain boundaries and random disorder produce the vortex pinning. Considering the large U 0 observed in the single crystal, we attempt to improve the pinning by adding random point disorder by 3 MeV proton irradiation with a fluence of 2 × 10 16 proton/cm 2 . The results show that, unlike other iron-based superconductors, the superconducting fraction is sharply reduced by irradiation. This fact indicates that the superconductivity in the system is extremely fragile to an increment in the disorder. The superconducting volume fraction in the irradiated crystal systematically recovers after removal disorder by thermal annealing, which evidences as to the observation of critical state in curves of magnetization versus magnetic field. No features related to a reentrant antiferromagnetic transition are observed for the irradiated sample.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Avalanche statistics of fluctuation-induced fluxes from the SLPM and the W7-AS stellarator

Measurements of fluctuating floating potentials and ion saturation currents at different radial locations in the Santander Linear Plasma Machine (Castellanos et al 2005 Plasma Phys. Control. Fusion47 2067) and at the edge of the W7-AS stellarator by means of radially movable Langmuir probes allow to infer the corresponding fluctuation-induced radial flux temporal series. Avalanche-like transport events are identified in the time series and statistically characterized in terms of avalanche size/duration/quiet-time distributions and size-duration scaling relations. Transport is diffusive in the inner and intermediate radial region of the SLPM r < r tr ≈ 2.6 cm, undergoing a transition at r tr , becoming non-diffusive in the outermost region of the device, r > r tr . Here, the results obtained at the edge of the W7-AS stellarator are similar to those found in SLPM for r > r tr , i.e. consistent with what would be expected for scale-free, self-similar plasma transport dynamics near a critical state.

Avalanches↗

DOE OSTI2020

Cooperative response of magnetism and superconductivity in the magnetic superconductor RbEuFe 4 As 4

Herein, we present a study of the magnetic-flux evolution in the magnetic superconductor RbEuFe 4 As 4 performed using magneto-optical imaging and magnetization measurements during field cooling and warming and magnetic field cycling at temperatures above and below the magnetic transition point, T$_m$. The vortex patterns emerging at T ≲ T$_m$ reveal that the Eu-spin subsystem serves as an internal pump of the magnetic flux while the superconducting critical current controls the delivery of magnetic-flux quanta into the bulk. The interplay of magnetic susceptibility amplifying the magnetic induction and vortex pinning attenuating the magnetic-flux entry results in a field- and temperature-dependent critical state that emulates a paramagnetic Meissner effect. The observed vortex dynamics corresponds to a nontrivial spatial current distribution and yields a self-consistent inhomogeneous enhancement of the sample magnetization.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Excitation spectra of quantum matter without quasiparticles. I. Sachdev-Ye-Kitaev models

Here, we study the low-frequency spectra of complex Sachdev-Ye-Kitaev models at general densities. The analysis applies also to SU(M) magnets with random exchange at large M. The spectral densities are computed by numerical analysis of the saddle-point equations on the real frequency ω axis at zero temperature T. The asymptotic low-ω behaviors are found to be in excellent agreement with the scaling dimensions of irrelevant operators which perturb the conformally invariant critical states. Of possible experimental interest is our computation of the universal spin spectral weight of the SU(M) magnets at low ω and T; this includes a contribution from the time reparametrization mode, which is the boundary graviton of the holographic dual. This analysis is extended to a random t-J model in the following paper [M. Tikhanovskaya et al., following paper, Phys. Rev. B 103, 075142 (2021)].

36 MATERIALS SCIENCE↗

DOE OSTI2021

Excitation spectra of quantum matter without quasiparticles. II. Random t - J models

Here, we present numerical solutions of the spectral functions of large dimension t -J models with random nearest neighbor exchange and global SU(M) spin rotation symmetry. The solutions are obtained from the saddle-point equations of the large dimension limit, followed by the large M limit. The same saddle point equations also apply to the model with all-to-all and random hopping and exchange. Such a t -J model realizes a deconfined critical state proposed as a model for the optimally doped cuprates. The large M theory involves Green’s functions for fractionalized spinons and holons carrying emergent U(1) gauge charges, obeying relations similar to those of the Sachdev-Ye-Kitaev (SYK) models. The low frequency spectral functions are compared with an analytic analysis of the operator scaling dimensions with good agreement. We also compute the low frequency and temperature behavior of experimentally observable gauge-invariant observables: the electron Green’s function, the local spin susceptibility and the optical conductivity, along with the temperature dependence of the d.c. resistivity. The time reparameterization soft mode (equivalent to the boundary graviton in holographically dual models of two-dimensional quantum gravity) makes important contributions to all observables and provides a linear-in-temperature contribution to the d.c. resistivity.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Quantum spin ice response to a magnetic field in the dipole-octupole pyrochlore Ce 2 Zr 2 O 7

The pyrochlore magnet Ce 2 Zr 2 O 7 has attracted much attention as a quantum spin ice candidate whose novelty derives in part from the dipolar-octupolar nature of the Ce 3+ pseudospin-1/2 degrees of freedom it possesses. We report heat capacity measurements on single crystal samples of Ce 2 Zr 2 O 7 down to T~0.1K in a magnetic field along the [$1,\bar{1},0$] direction. These measurements show that the broad hump in the zero-field heat capacity moves higher in temperature with increasing field strength and is split into two separate humps by the [$1,\bar{1},0$] magnetic field at ~2T. These separate features are due to the decomposition of the pyrochlore lattice into effectively decoupled chains for fields in this direction: One set of chains (α chains) is polarized by the field while the other (β chains) remains free. This situation is similar to that observed in the classical spin ices Ho 2 Ti 2 O 7 and Dy 2 Ti 2 O 7 , but with the twist that here the strong transverse exchange interactions produce substantial quantum effects. Our theoretical modeling suggests that the β chains are close to a critical state, with nearly-gapless excitations. We also report elastic and inelastic neutron scattering measurements on single crystal Ce 2 Zr 2 O 7 in [$1,\bar{1},0$] and [0,0,1] magnetic fields at temperatures down to T=0.03K. The elastic scattering behaves consistently with the formation of independent chains for a [$1,\bar{1},0$] field, while the [0,0,1] field produces a single field-induced elastic magnetic Bragg peak at (0,2,0) and equivalent wavevectors, indicating a polarized spin ice state for fields above ~3T. For both [$1,\bar{1},0$] and [0,0,1] magnetic fields, our inelastic neutron scattering results show an approximately dispersionless continuum of scattering that increases in both energy and intensity with increasing field strength. By modeling the complete set of experimental data using numerical linked cluster and semiclassical molecular dynamics calculations, we demonstrate the dominantly multipolar nature of the exchange interactions in Ce 2 Zr 2 O 7 and the smallness of the parameter θ, which controls the mixing between dipolar and octupolar degrees of freedom. Finally, these results support previous estimates of the microscopic exchange parameters and place strong constraints on the theoretical description of this prominent spin ice candidate.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2021

Distribution of blackouts in the power grid and the Motter and Lai model

Carreras, Dobson, and colleagues have studied empirical data on the sizes of the blackouts in real grids and modeled them with computer simulations using the direct current approximation. They have found that the resulting blackout sizes are distributed as a power law and suggested that this is because the grids are driven to the self-organized critical state. In contrast, more recent studies found that the distribution of cascades is bimodal resulting in either a very small blackout or a very large blackout, engulfing a finite fraction of the system. Here we reconcile the two approaches and investigate how the distribution of the blackouts changes with model parameters, including the tolerance criteria and the dynamic rules of failure of the overloaded lines during the cascade. Finally, we study the same problem for the Motter and Lai model and find similar results, suggesting that the physical laws of flow on the network are not as important as network topology, overload conditions, and dynamic rules of failure.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Transformer Health Monitoring via Synchrophasors

Traditional transformer protection schemes such as differential protection operate once the transformer is in a critical state. Proactive means of transformer health evaluation such as Sweep Frequency Response Analysis, can only be performed periodically with the transformer out-of-service. This work presents a framework where the health and structural integrity of transformers is monitored via synchrophasors in real-time. Synchrophasors and subspace estimation techniques are used to build reduced-order models which are then analyzed across multiple domains. A diagnostics algorithm is developed and tested via Matlab simulations. Test results are promising, opening up new prospects in transformer protection research.

cyber-physical security↗

DOE OSTI2022

Feynman-α analysis using BGO gamma-ray detector in UTR-KINKI reactor

In conventional reactor noise measurement based on neutron detection, a neutron detector must be placed as close to a core as possible, to observe a largest possible correlation amplitude. For most of reactors other than critical assemblies, however, the placement is hardly possible. We focused on an alternative reactor noise measurement using prompt gamma-rays having a long flight range, to overcome the above constraint. A Feynman-α analysis using a NaI(Tl) scintillation detector was previously performed in UTR-KINKI, however, white noise originating from radioactivation of the scintillator significantly degraded the correlation amplitude. In this study, another Feynman-α analysis using a BGO gamma-ray detector, which never suffers from any radioactivation, is performed. A series of Feynman-α analyses for a critical state and several subcritical states of UTR-KINKI reactor has been carried out using two BGO detectors and a BF{sub 3} neutron detector to determine prompt-neutron decay constant. In the present analysis, the dead-time effect of these detectors and the delayed-neutron effect are considered. The prompt-neutron decay constant determined from Feynman-α analysis based on gamma-ray detection agrees with that from the analysis based on neutron detection. The Feynman-α analysis based on detecting gamma rays appears to be able to determine prompt-neutron decay constant at least as efficiently as the conventional analysis detecting neutrons.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2022

On the novel 3-D neutron transport kinetic tRAPID algorithm and its validation

The Real-time Analysis for Particle-transport and In-situ Detection (RAPID) Code System, based on the Multi-stage Response-function Transport (MRT) methodology, allows for real-time simulation of nuclear systems based on 3-D continuous-energy particle transport. RAPID's steady-state (criticality) neutron transport algorithm is based on the Fission Matrix (FM) method, and has been extensively verified and validated against computational benchmarks and experiments. This paper introduces the novel 3-D time-dependent transport algorithm that has been implemented into the code, tRAPID, and its validation using the JSI TRIGA Mark-II reactor. tRAPID accurately and efficiently calculates neutron kinetics parameters (such as β{sub eff}, l{sub eff} , Λ, α{sub Rossi}) and 3-D time-dependent neutron fission source distribution and neutron importances for both prompt and delayed neutrons. tRAPID is used to simulate a rod insertion experiment performed at the JSI TRIGA Mark-II reactor, during which signals from four fission chambers at four different locations in the core were collected. The results demonstrate how tRAPID is capable of calculating detailed and accurate results with only a minimal use computational resources and time.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Cladding Degradation Model

This report begins with an evaluation of cladding degradation mechanisms deemed important to assessing barrier capability. Unlike similar efforts done in the past, this evaluation accounts for the hypothetical conditions associated with direct dual-purpose canister (DPC) disposal, including conditions resulting from a postulated, in-package, steady-state criticality event. A total of 16 cladding degradation mechanisms are examined assuming direct disposal of DPCs in two different hypothetical repositories: a saturated repository in shale and an unsaturated repository in alluvium.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗