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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 595 records · Page 33
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DOE OSTI2015

Phase 1/2 Trials of Temozolomide, Motexafin Gadolinium, and 60-Gy Fractionated Radiation for Newly Diagnosed Supratentorial Glioblastoma Multiforme: Final Results of RTOG 0513

Purpose: The purpose of phase 1 was to determine the maximum tolerated dose (MTD) of motexafin gadolinium (MGd) given concurrently with temozolomide (TMZ) and radiation therapy (RT) in patients with newly diagnosed supratentorial glioblastoma multiforme (GBM). Phase 2 determined whether this combination improved overall survival (OS) and progression-free survival (PFS) in GBM recursive partitioning analysis class III to V patients compared to therapies for recently published historical controls. Methods and Materials: Dose escalation in phase 1 progressed through 3 cohorts until 2 of 6 patients experienced dose-limiting toxicity or a dose of 5 mg/kg was reached. Once MTD was established, a 1-sided 1-sample log-rank test at significance level of .1 had 85% power to detect a median survival difference (13.69 vs 18.48 months) with 60 deaths over a 12-month accrual period and an additional 18 months of follow-up. OS and PFS were estimated using the Kaplan-Meier method. Results: In phase 1, 24 patients were enrolled. The MTD established was 5 mg/kg, given intravenously 5 days a week for the first 10 RT fractions, then 3 times a week for the duration of RT. The 7 patients enrolled in the third dose level and the 94 enrolled in phase 2 received this dose. Of these 101 patients, 87 were eligible and evaluable. Median survival time was 15.6 months (95% confidence interval [CI]: 12.9-17.6 months), not significantly different from that of the historical control (P=.36). Median PFS was 7.6 months (95% CI: 5.7-9.6 months). One patient (1%) experienced a grade 5 adverse event possibly related to therapy during the concurrent phase, and none experience toxicity during adjuvant TMZ therapy. Conclusions: Treatment was well tolerated, but median OS did not reach improvement specified by protocol compared to historical control, indicating that the combination of standard RT with TMZ and MGd did not achieve a significant survival advantage.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Pretreatment Modified Glasgow Prognostic Score Predicts Clinical Outcomes After Stereotactic Body Radiation Therapy for Early-Stage Non-Small Cell Lung Cancer

Purpose: This study aimed to evaluate the prognostic significance of the modified Glasgow Prognostic Score (mGPS) in patients with non-small cell lung cancer (NSCLC) who received stereotactic body radiation therapy (SBRT). Methods and Materials: Data from 165 patients who underwent SBRT for stage I NSCLC with histologic confirmation from January 1999 to September 2010 were collected retrospectively. Factors, including age, performance status, histology, Charlson comorbidity index, mGPS, and recursive partitioning analysis (RPA) class based on sex and T stage, were evaluated with regard to overall survival (OS) using the Cox proportional hazards model. The impact of the mGPS on cause of death and failure patterns was also analyzed. Results: The 3-year OS was 57.9%, with a median follow-up time of 3.5 years. A higher mGPS correlated significantly with poor OS (P<.001). The 3-year OS of lower mGPS patients was 66.4%, whereas that of higher mGPS patients was 44.5%. On multivariate analysis, mGPS and RPA class were significant factors for OS. A higher mGPS correlated significantly with lung cancer death (P=.019) and distant metastasis (P=.013). Conclusions: The mGPS was a significant predictor of clinical outcomes for SBRT in NSCLC patients.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

A Phase 2 Study of Concurrent Radiation Therapy, Temozolomide, and the Histone Deacetylase Inhibitor Valproic Acid for Patients With Glioblastoma

Purpose: Valproic acid (VPA) is an antiepileptic agent with histone deacetylase inhibitor (HDACi) activity shown to sensitize glioblastoma (GBM) cells to radiation in preclinical models. We evaluated the addition of VPA to standard radiation therapy (RT) plus temozolomide (TMZ) in patients with newly diagnosed GBM. Methods and Materials: Thirty-seven patients with newly diagnosed GBM were enrolled between July 2006 and April 2013. Patients received VPA, 25 mg/kg orally, divided into 2 daily doses concurrent with RT and TMZ. The first dose of VPA was given 1 week before the first day of RT at 10 to 15 mg/kg/day and subsequently increased up to 25 mg/kg/day over the week prior to radiation. VPA- and TMZ-related acute toxicities were evaluated using Common Toxicity Criteria version 3.0 (National Cancer Institute Cancer Therapy Evaluation Program) and Cancer Radiation Morbidity Scoring Scheme for toxicity and adverse event reporting (Radiation Therapy Oncology Group/European Organization for Research and Treatment). Results: A total of 81% of patients took VPA according to protocol. Median overall survival (OS) was 29.6 months (range: 21-63.8 months), and median progression-free survival (PFS) was 10.5 months (range: 6.8-51.2 months). OS at 6, 12, and 24 months was 97%, 86%, and 56%, respectively. PFS at 6, 12, and 24 months was 70%, 43%, and 38% respectively. The most common grade 3/4 toxicities of VPA in conjunction with RT/TMZ therapy were blood and bone marrow toxicity (32%), neurological toxicity (11%), and metabolic and laboratory toxicity (8%). Younger age and class V recursive partitioning analysis (RPA) results were significant for both OS and PFS. VPA levels were not correlated with grade 3 or 4 toxicity levels. Conclusions: Addition of VPA to concurrent RT/TMZ in patients with newly diagnosed GBM was well tolerated. Additionally, VPA may result in improved outcomes compared to historical data and merits further study.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Predicting Overall Survival After Stereotactic Ablative Radiation Therapy in Early-Stage Lung Cancer: Development and External Validation of the Amsterdam Prognostic Model

Purpose: A prognostic model for 5-year overall survival (OS), consisting of recursive partitioning analysis (RPA) and a nomogram, was developed for patients with early-stage non-small cell lung cancer (ES-NSCLC) treated with stereotactic ablative radiation therapy (SABR). Methods and Materials: A primary dataset of 703 ES-NSCLC SABR patients was randomly divided into a training (67%) and an internal validation (33%) dataset. In the former group, 21 unique parameters consisting of patient, treatment, and tumor factors were entered into an RPA model to predict OS. Univariate and multivariate models were constructed for RPA-selected factors to evaluate their relationship with OS. A nomogram for OS was constructed based on factors significant in multivariate modeling and validated with calibration plots. Both the RPA and the nomogram were externally validated in independent surgical (n=193) and SABR (n=543) datasets. Results: RPA identified 2 distinct risk classes based on tumor diameter, age, World Health Organization performance status (PS) and Charlson comorbidity index. This RPA had moderate discrimination in SABR datasets (c-index range: 0.52-0.60) but was of limited value in the surgical validation cohort. The nomogram predicting OS included smoking history in addition to RPA-identified factors. In contrast to RPA, validation of the nomogram performed well in internal validation (r{sup 2}=0.97) and external SABR (r{sup 2}=0.79) and surgical cohorts (r{sup 2}=0.91). Conclusions: The Amsterdam prognostic model is the first externally validated prognostication tool for OS in ES-NSCLC treated with SABR available to individualize patient decision making. The nomogram retained strong performance across surgical and SABR external validation datasets. RPA performance was poor in surgical patients, suggesting that 2 different distinct patient populations are being treated with these 2 effective modalities.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Survival Outcomes of Whole-Pelvic Versus Prostate-Only Radiation Therapy for High-Risk Prostate Cancer Patients With Use of the National Cancer Data Base

Purpose/Objectives: The addition of whole pelvic (WP) compared with prostate-only (PO) radiation therapy (RT) for clinically node-negative prostate cancer remains controversial. The purpose of our study was to evaluate the survival benefit of adding WPRT versus PO-RT for high-risk, node-negative prostate cancer, using the National Cancer Data Base (NCDB). Methods and Materials: Patients with high-risk prostate cancer treated from 2004 to 2006, with available data for RT volume, coded as prostate and pelvis (WPRT) or prostate alone (PO-RT) were included. Multivariate analysis (MVA) and propensity-score matched analysis (PSM) were performed. Recursive partitioning analysis (RPA) based on overall survival (OS) using Gleason score (GS), T stage, and pretreatment prostate-specific antigen (PSA) was also conducted. Results: A total of 14,817 patients were included: 7606 (51.3%) received WPRT, and 7211 (48.7%) received PO-RT. The median follow-up time was 81 months (range, 2-122 months). Under MVA, the addition of WPRT for high-risk patients had no OS benefit compared with PO-RT (HR 1.05; P=.100). On subset analysis, patients receiving dose-escalated RT also did not benefit from WPRT (HR 1.01; P=.908). PSM confirmed no survival benefit with the addition of WPRT for high-risk patients (HR 1.05; P=.141). In addition, RPA was unable to demonstrate a survival benefit of WPRT for any subset. Other prognostic factors for inferior OS under MVA included older age (HR 1.25; P<.001), increasing comorbidity scores (HR 1.46; P<.001), higher T stage (HR 1.17; P<.001), PSA (HR 1.81; P<.001), and GS (HR 1.29; P<.001), and decreasing median county household income (HR 1.15; P=.011). Factors improving OS included the addition of androgen deprivation therapy (HR 0.92; P=.033), combination external beam RT plus brachytherapy boost (HR 0.71; P<.001), and treatment at an academic/research institution (HR 0.84; P=.002). Conclusion: In the largest reported analysis of WPRT for patients with high-risk prostate cancer treated in the dose-escalated era, the addition of WPRT demonstrated no survival advantage compared with PO-RT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Factors Associated With Early Mortality in Patients Treated With Concurrent Chemoradiation Therapy for Locally Advanced Non-Small Cell Lung Cancer

Purpose: Concurrent chemoradiation therapy (con-CRT) is recommended for fit patients with locally advanced non-small cell lung cancer (LA-NSCLC) but is associated with toxicity, and observed survival continues to be limited. Identifying factors associated with early mortality could improve patient selection and identify strategies to improve prognosis. Methods and Materials: Analysis of a multi-institutional LA-NSCLC database consisting of 1245 patients treated with con-CRT in 13 institutions was performed to identify factors predictive of 180-day survival. Recursive partitioning analysis (RPA) was performed to identify prognostic groups for 180-day survival. Multivariate logistic regression analysis was used to create a clinical nomogram predicting 180-day survival based on important predictors from RPA. Results: Median follow-up was 43.5 months (95% confidence interval [CI]: 40.3-48.8) and 127 patients (10%) died within 180 days of treatment. Median, 180-day, and 1- to 5-year (by yearly increments) actuarial survival rates were 20.9 months, 90%, 71%, 45%, 32%, 27%, and 22% respectively. Multivariate analysis adjusted by region identified gross tumor volume (GTV) (odds ratio [OR] ≥100 cm{sup 3}: 2.61; 95% CI: 1.10-6.20; P=.029) and pulmonary function (forced expiratory volume in 1 second [FEV{sub 1}], defined as the ratio of FEV{sub 1} to forced vital capacity [FVC]) (OR <80%: 2.53; 95% CI: 1.09-5.88; P=.030) as significant predictors of 180-day survival. RPA resulted in a 2-class risk stratification system: low-risk (GTV <100 cm{sup 3} or GTV ≥100 cm{sup 3} and FEV{sub 1} ≥80%) and high-risk (GTV ≥100 cm{sup 3} and FEV{sub 1} <80%). The 180-day survival rates were 93% for low risk and 79% for high risk, with an OR of 4.43 (95% CI: 2.07-9.51; P<.001), adjusted by region. A clinical nomogram predictive of 180-day survival, incorporating FEV{sub 1}, GTV, N stage, and maximum esophagus dose yielded favorable calibration (R{sup 2} = 0.947). Conclusions: This analysis identified several risk factors associated with early mortality and suggests that future research in the optimization of pretreatment pulmonary function and/or functional lung avoidance treatment may alter the therapeutic ratio in this patient population.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Predictive Factor Analysis of Response-Adapted Radiation Therapy for Chemotherapy-Sensitive Pediatric Hodgkin Lymphoma: Analysis of the Children's Oncology Group AHOD 0031 Trial

Purpose: To evaluate whether clinical risk factors could further distinguish children with intermediate-risk Hodgkin lymphoma (HL) with rapid early and complete anatomic response (RER/CR) who benefit significantly from involved-field RT (IFRT) from those who do not, and thereby aid refinement of treatment selection. Methods and Materials: Children with intermediate-risk HL treated on the Children's Oncology Group AHOD 0031 trial who achieved RER/CR with 4 cycles of chemotherapy, and who were randomized to 21-Gy IFRT or no additional therapy (n=716) were the subject of this study. Recursive partitioning analysis was used to identify factors associated with clinically and statistically significant improvement in event-free survival (EFS) after randomization to IFRT. Bootstrap sampling was used to evaluate the robustness of the findings. Result: Although most RER/CR patients did not benefit significantly from IFRT, those with a combination of anemia and bulky limited-stage disease (n=190) had significantly better 4-year EFS with the addition of IFRT (89.3% vs 77.9% without IFRT; P=.019); this benefit was consistently reproduced in bootstrap analyses and after adjusting for other prognostic factors. Conclusion: Although most patients achieving RER/CR had favorable outcomes with 4 cycles of chemotherapy alone, those children with initial bulky stage I/II disease and anemia had significantly better EFS with the addition of IFRT as part of combined-modality therapy. Further work evaluating the interaction of clinical and biologic factors and imaging response is needed to further optimize and refine treatment selection.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

A fast algorithm for sparse matrix computations related to inversion

We have developed a fast algorithm for computing certain entries of the inverse of a sparse matrix. Such computations are critical to many applications, such as the calculation of non-equilibrium Green’s functions G{sup r} and G{sup <} for nano-devices. The FIND (Fast Inverse using Nested Dissection) algorithm is optimal in the big-O sense. However, in practice, FIND suffers from two problems due to the width-2 separators used by its partitioning scheme. One problem is the presence of a large constant factor in the computational cost of FIND. The other problem is that the partitioning scheme used by FIND is incompatible with most existing partitioning methods and libraries for nested dissection, which all use width-1 separators. Our new algorithm resolves these problems by thoroughly decomposing the computation process such that width-1 separators can be used, resulting in a significant speedup over FIND for realistic devices — up to twelve-fold in simulation. The new algorithm also has the added advantage that desired off-diagonal entries can be computed for free. Consequently, our algorithm is faster than the current state-of-the-art recursive methods for meshes of any size. Furthermore, the framework used in the analysis of our algorithm is the first attempt to explicitly apply the widely-used relationship between mesh nodes and matrix computations to the problem of multiple eliminations with reuse of intermediate results. This framework makes our algorithm easier to generalize, and also easier to compare against other methods related to elimination trees. Finally, our accuracy analysis shows that the algorithms that require back-substitution are subject to significant extra round-off errors, which become extremely large even for some well-conditioned matrices or matrices with only moderately large condition numbers. When compared to these back-substitution algorithms, our algorithm is generally a few orders of magnitude more accurate, and our produced round-off errors stay at a reasonable level.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Adaptive error covariances estimation methods for ensemble Kalman filters

This paper presents a computationally fast algorithm for estimating, both, the system and observation noise covariances of nonlinear dynamics, that can be used in an ensemble Kalman filtering framework. The new method is a modification of Belanger's recursive method, to avoid an expensive computational cost in inverting error covariance matrices of product of innovation processes of different lags when the number of observations becomes large. When we use only product of innovation processes up to one-lag, the computational cost is indeed comparable to a recently proposed method by Berry–Sauer's. However, our method is more flexible since it allows for using information from product of innovation processes of more than one-lag. Extensive numerical comparisons between the proposed method and both the original Belanger's and Berry–Sauer's schemes are shown in various examples, ranging from low-dimensional linear and nonlinear systems of SDEs and 40-dimensional stochastically forced Lorenz-96 model. Our numerical results suggest that the proposed scheme is as accurate as the original Belanger's scheme on low-dimensional problems and has a wider range of more accurate estimates compared to Berry–Sauer's method on L-96 example.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Numerical methods for high-dimensional probability density function equations

In this paper we address the problem of computing the numerical solution to kinetic partial differential equations involving many phase variables. These types of equations arise naturally in many different areas of mathematical physics, e.g., in particle systems (Liouville and Boltzmann equations), stochastic dynamical systems (Fokker–Planck and Dostupov–Pugachev equations), random wave theory (Malakhov–Saichev equations) and coarse-grained stochastic systems (Mori–Zwanzig equations). We propose three different classes of new algorithms addressing high-dimensionality: The first one is based on separated series expansions resulting in a sequence of low-dimensional problems that can be solved recursively and in parallel by using alternating direction methods. The second class of algorithms relies on truncation of interaction in low-orders that resembles the Bogoliubov–Born–Green–Kirkwood–Yvon (BBGKY) framework of kinetic gas theory and it yields a hierarchy of coupled probability density function equations. The third class of algorithms is based on high-dimensional model representations, e.g., the ANOVA method and probabilistic collocation methods. A common feature of all these approaches is that they are reducible to the problem of computing the solution to high-dimensional equations via a sequence of low-dimensional problems. The effectiveness of the new algorithms is demonstrated in numerical examples involving nonlinear stochastic dynamical systems and partial differential equations, with up to 120 variables.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

A stable high-order perturbation of surfaces method for numerical simulation of diffraction problems in triply layered media

The accurate numerical simulation of linear waves interacting with periodic layered media is a crucial capability in engineering applications. In this contribution we study the stable and high-order accurate numerical simulation of the interaction of linear, time-harmonic waves with a periodic, triply layered medium with irregular interfaces. In contrast with volumetric approaches, High-Order Perturbation of Surfaces (HOPS) algorithms are inexpensive interfacial methods which rapidly and recursively estimate scattering returns by perturbation of the interface shape. In comparison with Boundary Integral/Element Methods, the stable HOPS algorithm we describe here does not require specialized quadrature rules, periodization strategies, or the solution of dense non-symmetric positive definite linear systems. In addition, the algorithm is provably stable as opposed to other classical HOPS approaches. With numerical experiments we show the remarkable efficiency, fidelity, and accuracy one can achieve with an implementation of this algorithm.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Memory-optimized shift operator alternating direction implicit finite difference time domain method for plasma

Through introducing the alternating direction implicit (ADI) technique and the memory-optimized algorithm to the shift operator (SO) finite difference time domain (FDTD) method, the memory-optimized SO-ADI FDTD for nonmagnetized collisional plasma is proposed and the corresponding formulae of the proposed method for programming are deduced. In order to further the computational efficiency, the iteration method rather than Gauss elimination method is employed to solve the equation set in the derivation of the formulae. Complicated transformations and convolutions are avoided in the proposed method compared with the Z transforms (ZT) ADI FDTD method and the piecewise linear JE recursive convolution (PLJERC) ADI FDTD method. The numerical dispersion of the SO-ADI FDTD method with different plasma frequencies and electron collision frequencies is analyzed and the appropriate ratio of grid size to the minimum wavelength is given. The accuracy of the proposed method is validated by the reflection coefficient test on a nonmagnetized collisional plasma sheet. The testing results show that the proposed method is advantageous for improving computational efficiency and saving computer memory. The reflection coefficient of a perfect electric conductor (PEC) sheet covered by multilayer plasma and the RCS of the objects coated by plasma are calculated by the proposed method and the simulation results are analyzed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

A generalized approximate control variate framework for multifidelity uncertainty quantification

We describe and analyze a variance reduction approach for Monte Carlo (MC) sampling that accelerates the estimation of statistics of computationally expensive simulation models using an ensemble of models with lower cost. These lower cost models — which are typically lower fidelity with unknown statistics — are used to reduce the variance in statistical estimators relative to a MC estimator with equivalent cost. We derive the conditions under which our proposed approximate control variate framework recovers existing multifidelity variance reduction schemes as special cases. We demonstrate that existing recursive/nested strategies are suboptimal because they use the additional low-fidelity models only to efficiently estimate the unknown mean of the first low-fidelity model. As a result, they cannot achieve variance reduction beyond that of a control variate estimator that uses a single low-fidelity model with known mean. However, there often exists about an order-of-magnitude gap between the maximum achievable variance reduction using all low-fidelity models and that achieved by a single low-fidelity model with known mean. We show that our proposed approach can exploit this gap to achieve greater variance reduction by using non-recursive sampling schemes. The proposed strategy reduces the total cost of accurately estimating statistics, especially in cases where only low-fidelity simulation models are accessible for additional evaluations. Several analytic examples and an example with a hyperbolic PDE describing elastic wave propagation in heterogeneous media are used to illustrate the main features of the methodology.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Permutation-adapted complete and independent basis for atomic cluster expansion descriptors

Atomic cluster expansion (ACE) methods provide a systematic way to describe particle local environments of arbitrary body order. For practical applications it is often required that the basis of cluster functions be symmetrized with respect to rotations and permutations. Existing methodologies yield sets of symmetrized functions that are over-complete. These methodologies thus require an additional numerical procedure, such as singular value decomposition (SVD), to eliminate redundant functions. In this work, it is shown that analytical linear relationships for subsets of cluster functions may be derived using recursion and permutation properties of generalized Wigner symbols. From these relationships, subsets (blocks) of cluster functions can be selected such that, within each block, functions are guaranteed to be linearly independent. It is conjectured that this block-wise independent set of permutation-adapted rotation and permutation invariant (PA-RPI) functions forms a complete, independent basis for ACE. Along with the first analytical proofs of block-wise linear dependence of ACE cluster functions and other theoretical arguments, numerical results are offered to demonstrate this. The utility of the method is demonstrated in the development of an ACE interatomic potential for tantalum. Using the new basis functions in combination with Bayesian compressive sensing sparse regression, some high degree descriptors are observed to persist and help achieve high-accuracy models.

Angular momentum↗
DOE OSTI2025

Multi-frequency progressive refinement for learned inverse scattering

Interpreting scattered acoustic and electromagnetic wave patterns is a computational task that enables remote imaging in a number of important applications, including medical imaging, geophysical exploration, sonar and radar detection, and nondestructive testing of materials. However, accurately and stably recovering an inhomogeneous medium from far-field scattered wave measurements is a computationally difficult problem, due to the nonlinear and non-local nature of the forward scattering process. We design a neural network, called Multi-Frequency Inverse Scattering Network (MFISNet), and a training method to approximate the inverse map from far-field scattered wave measurements at multiple frequencies. We consider three variants of MFISNet, with the strongest performing variant inspired by the recursive linearization method — a commonly used technique for stably inverting scattered wavefield data — that progressively refines the estimate with higher frequency content. MFISNet outperforms past methods in regimes with high-contrast, heterogeneous large objects, and inhomogeneous unknown backgrounds.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Joint state-parameter estimation for the reduced fracture model via the united filter

Here, in this paper, we introduce an effective United Filter method for jointly estimating the solution state and physical parameters in flow and transport problems within fractured porous media. Fluid flow and transport in fractured porous media are critical in subsurface hydrology, geophysics, and reservoir geomechanics. Reduced fracture models, which represent fractures as lower-dimensional interfaces, enable efficient multi-scale simulations. However, reduced fracture models also face accuracy challenges due to modeling errors and uncertainties in physical parameters such as permeability and fracture geometry. To address these challenges, we propose a United Filter method, which integrates the Ensemble Score Filter (EnSF) for state estimation with the Direct Filter for parameter estimation. EnSF, based on a score-based diffusion model framework, produces ensemble representations of the state distribution without deep learning. Meanwhile, the Direct Filter, a recursive Bayesian inference method, estimates parameters directly from state observations. The United Filter combines these methods iteratively: EnSF estimates are used to refine parameter values, which are then fed back to improve state estimation. Numerical experiments demonstrate that the United Filter method surpasses the state-of-the-art Augmented Ensemble Kalman Filter, delivering more accurate state and parameter estimation for reduced fracture models. This framework also provides a robust and efficient solution for PDE-constrained inverse problems with uncertainties and sparse observations.

Bayesian inference↗
DOE OSTI2026

A score-based diffusion model approach for adaptive learning of stochastic partial differential equation solutions

In this paper, we propose a novel framework for adaptively learning the time-evolving solutions of stochastic partial differential equations (SPDEs) using score-based diffusion models within a recursive Bayesian inference setting. SPDEs play a central role in modeling complex physical systems under uncertainty, but their numerical solutions often suffer from model errors and reduced accuracy due to incomplete physical knowledge and environmental variability. To address these challenges, we encode the governing physics into the score function of a diffusion model using simulation data and incorporate observational information via a likelihood-based correction in a reverse-time stochastic differential equation. This enables adaptive learning through iterative refinement of the solution as new data becomes available. To improve computational efficiency in high-dimensional settings, we introduce the ensemble score filter, a training-free approximation of the score function designed for real-time inference. Numerical experiments on benchmark SPDEs demonstrate the accuracy and robustness of the proposed method under sparse and noisy observations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

A correlation based fault detection method for short circuits in battery packs

Here this paper presents a fault detection method for short circuits based on the correlation coefficient of voltage curves. The proposed method utilizes the direct voltage measurements from the battery cells, and does not require any additional hardware or effort in modeling during fault detection. Moreover, the inherent mathematical properties of the correlation coefficient ensure the robustness of this method as the battery pack ages or is imbalanced in real applications. In order to apply this method online, the recursive moving window correlation coefficient calculation is adopted to maintain the detection sensitivity to faults during operation. An additive square wave is designed to prevent false positive detections when the batteries are at rest. The fault isolation can be achieved by identifying the overlapped cell in the correlation coefficients with fault flags. Simulation and experimental results validated the feasibility and demonstrated the advantages of this method.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗