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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The Princess Project: From Differential to Integral Experiments

Following the shutdown of the CEA Valduc experimental facilities, where, for more than 50 years, IRSN used to perform experiments related to criticality safety, IRSN initiated a new project named PRINCESS (PRoject for IRSN Neutron physics and Criticality Experimental data Supporting Safety). The objective is to continue collecting experimental data necessary for the IRSN missions in nuclear safety. For this purpose, collaborations with various national and international laboratories have been established. The PRINCESS project covers various nuclear physics fields from nuclear data to criticality-safety and reactor physics providing information to both differential and integral data improvements.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

IER-517: Molybdenum Optimized Benchmark System Demonstrating Integral Correlations (MOBY DICK)

Nuclear criticality experiments are essential to the validation of nuclear data used in simulation software. The quality of nuclear data becomes paramount as simulation software becomes more relied upon for criticality safety studies and designs of nuclear systems. To improve the quality of nuclear data, experimenters can design critical experiments that are sensitive to isotope reaction pairs in materials of interest. The efforts conducted by the Organisation for Economic Co-operation and Development - Nuclear Energy Agency (OECD-NEA) Working Party on Nuclear Criticality Safety (WPNCS) Subgroup 8: Preservation of Expert Knowledge and Judgement Applied to Criticality Benchmarks (SG8) to categorize benchmarks according to their usefulness for nuclear data validation have been of great importance. Based on the OECD studies benchmark experiments included in the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook are concisely used by nuclear data evaluators, criticality safety engineers and others to validate nuclear data and simulation results. A lack of benchmarks sensitive to molybdenum in the (ICSBEP), particularly in the intermediate range, was noted by Los Alamos National Laboratory (LANL), the French Institut de Radioprotection et de Sûreté Nucléaire (IRSN), and Y-12 National Security Site prompting them to submit a joint integral experiment request to the Nuclear Criticality Safety Program (NCSP) in 2019. The request included both HEU and Plutonium systems in order to validate differential nuclear data focusing on the intermediate energy range but also includes thermal and fast configurations. This document represents the preliminary design work for a series of molybdenum integral experiments known as Molybdenum Optimized Benchmark System Demonstrating Integral Correlations (MOBY DICK).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

KR Persei, a Mid-F Eclipsing Binary with a One-day Period

KR Per is a partially eclipsing binary with an orbital period of 0.9960798 days, very close to one sidereal day, making it difficult to obtain extensive phase coverage in a reasonable amount of time. We used the Wilson–Devinney program to determine its orbital elements and stellar absolute dimensions from recently acquired radial velocities and differential BVRI observations that were supplemented with previous differential UBV measurements and published times of minima. The two components are each F5 V stars with masses of 1.466±0.015 M{sub ⊙} and 1.458±0.015 M{sub ⊙}. The radii are 1.855±0.021 R{sub ⊙} and 1.824±0.022 R{sub ⊙}. The orbital period of the eclipsing system is variable and more times of minima observations are needed. A comparison with evolutionary tracks indicates that the system has an age of 2.1 ± 0.1 Gyr.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

TINES - Time Integration, Newton and Eigen Solver v. 1.0

SAND2021-1505 O. TINES is an open source software providing math infrastructure for solving many stiff time ordinary differential equations (ODEs) and/or differential algebraic equations (DAEs) using a batch hierarchical parallelism. The code is written using a parallel programming model (i.e., Kokkos) to future-proof the next generation parallel computing platforms such as GPU accelerators. This code is developed to support Exascale Catalytic Chemistry (ECC) Project. The code provides fundamental math helpers that can aid other research projects. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Kim, Kyungjoo↗
DOE OSTI2024

Parallel Variable Population Multi-Objective Optimizer (pvpmoo) v1.0

This is a parallel variable population multi-objective optimizer with an adaptive unified differential evolution algorithm or a genetic algorithm. It can also be used for single objective optimization. Some features of this code include: 1) The population size varies from generation to generation to save the total # of objective function evaluations. 2) The population is uniformly distributed to a number of parallel processors for simultaneous objective function evaluation. 3) The objective function evaluation can be attained from an external simulation program with control variables in its input file and objectives calculated from its output files. 4) The optimizer includes an adaptive unified differential evolution algorithm and a real value genetic algorithm. The parameters in the unified differential evolution algorithm can be chosen to attain any mutation schemes in the published literature.

Qiang, Ji↗
DOE OSTI2024

Differentiable Multiphysics Codes: A Breakthrough Technology for Simulation and Computing

This document summarizes the findings of a strategic planning exercise commissioned by the Weapons Simulation and Computing, Computational Physics (WSC/CP) program at the Lawrence Livermore National Laboratory (LLNL) in FY24. During the year, the committee met with multiple stakeholder communities to gather input, opinions, suggestions and concerns which have been incorporated throughout this document. The key findings from this exercise are summarized: • The development of multiphysics modelling and simulation (mod/sim) codes and software technologies, their deployment on exascale compute platforms, and their broad adoption across the NNSA is a major success of the Advanced Simulation and Computing (ASC) program and the Exascale Computing Project (ECP). Sustained investment in these core technologies is essential. • Today’s state of the art involves running ensembles of O(100K) simulations to perform uncertainty quantification (UQ) and design studies using multiple statistical methods such as Bayesian optimization to understand sensitivities of our models and explore parameterized design spaces. Even with exascale computing, we are practically limited to O(10) parameters in these studies since the number of simulations required to sample the space scales exponentially with the number of design parameters. • The data from these simulation ensembles is increasingly being used to train machine learned (ML) surrogates (or reduced order models, ROMs) which can then be used for optimization or real time design exploration. However, the trained surrogates are still limited in the number of parameters they can represent due to the sampling limitations previously noted. • Augmenting our suite of integrated multiphysics simulation codes, both current and emerging, with the ability to compute gradients (solution derivatives) of arbitrary simulation outputs with respect to (some or all) simulation inputs would be a breakthrough technology, opening the door to a new era of efficient and automated inverse design based on verified and validated mod/sim capabilities. • This capability, which we refer to as differentiable multiphysics codes (DMCs), would revolutionize both UQ and optimization studies by breaking the curse of dimensionality that presently limits our “gradient-free” ensemble based computing approach. A similar breakthrough occurred in the AI/ML community once the ability to compute gradients of arbitrary loss functions using back-propagation became commonplace. Gradient information from the multiphysics codes can also be used to dramatically improve the efficiency and scale of training of ML/ROM surrogates for rapid assessments. • Achieving this in our suite of codes will be a grand challenge, similar to the amount of effort that was required to transition from CPU to GPU computing. It will require buy-in from the entire WSC/CP program and beyond, including all integrated codes, physics and engineering models, third-party library dependencies and performance portability abstractions. It will also require investment in research and development of numerical methods for computing adjoints of coupled physics across multiple adaptively refined moving meshes and of stochastic (Monte Carlo) and mesh free (SPH) methods. • New software and numerical techniques, largely pioneered by the AI/ML community, make this feasible. Chief among these is automatic differentiation (AD), the ability to employ AD at point-wise locations in a physics calculation (instead of traditional black-box approaches) and the ability to perform “back-propagation in time” (or reverse mode AD) for non-linear partial differential equations (PDEs). Fundamentally, the conclusion of this strategic planning exercise is that the time is right to undertake a large scale effort in WSC, centered on the existing integrated codes, to continue the natural evolution of mod/sim in the age of AI/ML. Instead of attempting to replace mod/sim with purely data driven AI/ML models, we believe the key to success is to integrate AI/ML by building on top of the decades of hard-won knowledge and the verified/validated multiphysics modelling capability that is the hallmark of the ASC program.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

First Temperature Profile of a Stellar Flare Using Differential Chromatic Refraction

We present the first derivation of a stellar flare temperature profile from single-band photometry. Stellar flare DWF 030225.574−545707.45129 was detected in 2015 by the Dark Energy Camera as part of the Deeper, Wider, Faster program. The brightness (Δm g = −6.12) of this flare, combined with the high air mass (1.45 ≲ X ≲ 1.75) and blue filter (DES g, 398–548 nm) in which it was observed, provided ideal conditions to measure the zenithward apparent motion of the source due to differential chromatic refraction (DCR) and, from that, infer the effective temperature of the event. We model the flare’s spectral energy distribution as a blackbody to produce the constraints on flare temperature and geometric properties derived from single-band photometry. We additionally demonstrate how simplistic assumptions on the flaring spectrum, as well as on the evolution of flare geometry, can result in solutions that overestimate the effective temperature. Exploiting DCR enables studying chromatic phenomena with ground-based astrophysical surveys, and stellar flares on M dwarfs are a particularly enticing target for such studies due to their ubiquity across the sky and the heightened color contrast between their red quiescent photospheres and the blue flare emission. Our novel method will enable similar temperature constraints for a large sample of objects in upcoming photometric surveys like the Vera C. Rubin Legacy Survey of Space and Time.

Clarke, Riley W. [University of Delaware, Newark, ↗
DOE OSTI2020

DOE/NNSA Nuclear Criticality Safety Program – Brief Overview [Slides]

This presentation discusses nuclear data measurements and evaluation work for the NCSP. The objective of the NCSP is to provide measured and evaluated thermal, resonance, unresolved resonance, and fast region cross section data to address the priority NCSP nuclear data needs. It also discusses its vision which is to address multiple Nuclear Data 5- and 10-year goals and attributes identified in the NCSP. The intended final product is for rigorous ENDF/B evaluations to be produced from cross section measurements and analyses. It also discusses NCSP integral experiments and differential experiments in addition to NCSP support of SCALE in the future.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Deep Learning Explicit Differentiable Predictive Control Laws for Buildings

We present a differentiable predictive control (DPC) methodology for learning constrained control laws for unknown nonlinear systems. DPC poses an approximate solution to multiparametric programming problems emerging from explicit nonlinear model predictive control (MPC). Contrary to approximate MPC, DPC does not require supervision by an expert controller. Instead, a system dynamics model is learned from a small dataset of recorded observations of the perturbed system's dynamics and the control law is optimized offline by interaction with the learned system model. The DPC method is based on two sequential steps, i) system identification using a constrained neural state-space model, and ii) optimization of an explicit control law parametrized by another neural network in closed-loop simulation with the identified neural state-space model. The combination of a differentiable closed-loop system and penalty methods for constraint handling of system outputs and inputs allows us to optimize the control law's parameters directly by backpropagating economic MPC loss through the learned system model. By incorporating domain knowledge and leveraging established techniques from optimal control, our method leverages deep neural networks as nonlinear function approximators for system identification and control while avoiding concomitant costs of intractably large datasets, and computationally expensive over-parametrized models. The scalability, data efficiency, and constrained optimal control capability of the proposed DPC method are demonstrated in simulation using a multi-zone building emulator.

Drgona, Jan↗
DOE OSTI2025

Boundary-Layer-Coupled and Decoupled Clouds in Global Storm-Resolving Models: Comparisons With the ARM Observations

The accurate representation of interactions between clouds and planetary boundary layer (PBL) is a persistent challenge in climate models, critical for simulating surface energy budget. The emergence of kilometer-grid-scale global storm resolving models (GSRMs) offers the potential for enhanced details of PBL processes in these complex interactions. This study evaluates the representation of PBL-coupled and decoupled clouds in nine GSRM simulations against extensive ground-based observations by the Department of Energy Atmospheric Radiation Measurement (ARM) program, across six sites encompassing diverse regimes such as marine and continental environments in tropics and midlatitude. By differentiating coupling based on the relative positions between cloud bases and PBL tops, our analysis focuses on the simulation of PBL height, cloud frequency, position and vertical extent. The GSRMs generally exhibit commendable agreements with observed cloud structures and PBL diurnal cycles across different ARM sites. In contrast to the relatively consistent representation of decoupled clouds, discrepancies exist between the simulated and the observed coupled clouds, particularly in areas of intense convection, for example, over tropical rainforests and mountainous regions. These biases are probably associated with the models' tendency to underestimate the boundary layer humidity and the frequency of coupled clouds within different ranges of PBL heights. This study underscores the importance for continuous improvements in the representation of boundary layer and convection within these global kilometer-grid-scale models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Generic Discretization Library

The GenDiL library is a collection of C++ software abstractions designed to discretize and solve partial differential equations (PDEs) for high-performance computing (HPC) applications. Its primary focus is on modern C++ generic programming, which helps ensure portability across various hardware architectures. The central idea behind the library is to provide building blocks for numerical algorithms-such as discretization methods and iteration patterns-so that domain experts can focus on the math, rather than the low-level details of hardware or implementation. By defining abstractions for data types, iteration over computational grids, and scheduling of operations, the library isolates the high-level PDE algorithms from the platform-specific optimizations needed to achieve efficient performance.

Dudouit, Yohann [Lawrence Livermore National Labor↗
DOE OSTI2022

A MUC 5 B Gene Polymorphism, rs35705950-T, Confers Protective Effects Against COVID-19 Hospitalization but Not Severe Disease or Mortality

A common MUC5B gene polymorphism, rs35705950-T, is associated with idiopathic pulmonary fibrosis (IPF), but its role in severe acute respiratory syndrome coronavirus 2 infection and disease severity is unclear. To assess whether rs35705950-T confers differential risk for clinical outcomes associated with coronavirus disease (COVID-19) infection among participants in the Million Veteran Program (MVP). The MUC5B rs35705950-T allele was directly genotyped among MVP participants; clinical events and comorbidities were extracted from the electronic health records. Associations between the incidence or severity of COVID-19 and rs35705950-T were analyzed within each ancestry group in the MVP followed by transancestry meta-analysis. Replication and joint meta-analysis were conducted using summary statistics from the COVID-19 Host Genetics Initiative (HGI). Sensitivity analyses with adjustment for additional covariates (body mass index, Charlson comorbidity index, smoking, asbestosis, rheumatoid arthritis with interstitial lung disease, and IPF) and associations with post–COVID-19 pneumonia were performed in MVP subjects. The MUC5B variant rs35705950-T may confer protection in COVID-19 hospitalizations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A transcriptome software comparison for the analyses of treatments expected to give subtle gene expression responses

Background: In this comparative study we evaluate the performance of four software tools: DNAstar-D (DESeq2), DNAstar-E (edgeR), CLC Genomics and Partek Flow for identification of differentially expressed genes (DEGs) using a transcriptome of E. coli. The RNA-seq data are from the effect of below-background radiation 5.5 nGy total dose (0.2nGy/hr) on E. coli grown shielded from natural radiation 655 m below ground in a pre-World War II steel vault. The gene expression response to three supplemented sources of radiation designed to mimic natural background, 1952 – 5720 nGy in total dose (71–208 nGy/hr), are compared to this “radiation-deprived” treatment. In addition, RNA-seq data of Caenorhabditis elegans nematode from similar radiation treatments was analyzed by three of the software packages. Results: In E. coli, the four software programs identified one of the supplementary sources of radiation (KCl) to evoke about 5 times more transcribed genes than the minus-radiation treatment (69–114 differentially expressed genes, DEGs), and so the rest of the analyses used this KCl vs “Minus” comparison. After imposing a 30-read minimum cutoff, one of the DNAStar options shared two of the three steps (mapping, normalization, and statistic) with Partek Flow (they both used median of ratios to normalize and the DESeq2 statistical package), and these two programs identified the highest number of DEGs in common with each other (53). In contrast, when the programs used different approaches in each of the three steps, between 31 and 40 DEGs were found in common. Regarding the extent of expression differences, three of the four programs gave high fold-change results (15–178 fold), but one (DNAstar’s DESeq2) resulted in more conservative fold-changes (1.5–3.5). In a parallel study comparing three qPCR commercial validation software programs, these programs also gave variable results as to which genes were significantly regulated. Similarly, the C. elegans analysis showed exaggerated fold-changes in CLC and DNAstar’s edgeR while DNAstar-D was more conservative. Conclusions: Regarding the extent of expression (fold-change), and considering the subtlety of the very low level radiation treatments, in E. coli three of the four programs gave what we consider exaggerated fold-change results (15 – 178 fold), but one (DNAstar’s DESeq2) gave more realistic fold-changes (1.5–3.5). When RT-qPCR validation comparisons to transcriptome results were carried out, they supported the more conservative DNAstar-D’s expression results. When another model organism’s (nematode) response to these radiation differences was similarly analyzed, DNAstar-D also resulted in the most conservative expression patterns. Therefore, we would propose DESeq2 (“DNAstar-D”) as an appropriate software tool for differential gene expression studies for treatments expected to give subtle transcriptome responses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Clean Energy Employment Impacts and Occupational Analyses: Building Envelope & Electrification Upgrades

Under the Communities LEAP (Local Energy Action Program) Pilot, the U.S. Department of Energy (DOE) is working with a group of LEAP communities to bolster workforce development initiatives and support the growth of local employment in the clean energy economy. Through this resource, DOE seeks to provide participating communities with an overview of the types of occupations that could be affected by investments in building envelope and building electrification upgrades in existing building stock - differentiating between the residential and commercial sectors. This occupational analysis is intended to be used by communities to inform workforce initiatives (e.g., local training and education programs) as they implement building energy efficiency and electrification projects at scale.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Insights of Molecular Mechanism of Xylem Development in Five Black Poplar Cultivars

Black poplar (Populus deltoides, P. nigra, and their hybrids) is the main poplar cultivars in China. It offers interesting options of large-scale biomass production for bioenergy due to its rapid growth and high yield. Poplar wood properties were associated with chemical components and physical structures during wood formation. In this study, five poplar cultivars, P. euramericana ‘Zhonglin46’ (Pe1), P. euramericana ‘Guariento’ (Pe2), P. nigra ‘N179’ (Pn1), P. deltoides ‘Danhong’ (Pd1), and P. deltoides ‘Nanyang’ (Pd2), were used to explore the molecular mechanism of xylem development. We analyzed the structural differences of developing xylem in the five cultivars and profiled the transcriptome-wide gene expression patterns through RNA sequencing. The cross sections of the developing xylem showed that the cell wall thickness of developed fiber in Pd1 was thickest and the number of xylem vessels of Pn1 was the least. A total of 10,331 differentially expressed genes were identified among 10 pairwise comparisons of the five cultivars, most of them were related to programmed cell death and secondary cell wall thickening. K-means cluster analysis and Gene Ontology enrichment analysis showed that the genes highly expressed in Pd1 were related to nucleotide decomposition, metabolic process, transferase, and microtubule cytoskeleton; whereas the genes highly expressed in Pn1 were involved in cell wall macromolecule decomposition and polysaccharide binding processes. Based on a weighted gene co-expression network analysis, a large number of candidate regulators for xylem development were identified. And their potential regulatory roles to cell wall biosynthesis genes were validated by a transient overexpression system. This study provides a set of promising candidate regulators for genetic engineering to improve feedstock and enhance biofuel conversion in the bioenergy crop Populus.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Coupled Time-Lapse Full-Waveform Inversion for Subsurface Flow Problems Using Intrusive Automatic Differentiation

We describe a novel framework for estimating subsurface properties, such as rock permeability and porosity, from time-lapse observed seismic data by coupling full-waveform inversion (FWI), subsurface flow processes, and rock physics models. For the inverse modeling, we handle the back propagation of gradients by an intrusive automatic differentiation strategy that offers three levels of user control: (1) At the wave physics level, we adopted the discrete adjoint method in order to use our existing high-performance FWI code; (2) at the rock physics level, we used built-in automatic differentiation operators from the TensorFlow backend; (3) at the flow physics level, we implemented customized partial differential equation (PDE) operators for the multiphase flow equations. The three-level coupled inversion strategy strikes a good balance between computational efficiency and programming efforts, and when the gradients are chained together, it constitutes a coupled inverse system. Our numerical experiments demonstrate that the three-level coupled inverse problem is superior in terms of accuracy to a traditional decoupled inversion strategy. Additionally, our method is able to simultaneously invert for parameters in empirical relationships such as the rock physics models. Our proposed inverted model can be used for reservoir performance prediction and reservoir management/optimization purposes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

CHARGED-CURRENT DOUBLE-DIFFERENTIAL CROSS SECTION MEASUREMENT OF ELECTRON NEUTRINOS IN LOW RECOIL REGION ON HYDROCARBON AT ∼7 GEV

Measuring neutrino mixing angles, especially the CP violation phase and mass hierarchy, is one of the priorities of the neutrino community and long baseline neutrino oscillation programs, such as T2K and NOvA, provided the most precise measurements to date. One of the dominating uncertainties of the measurements is the neutrino interaction model due to the difficulty of modeling the nuclear effects from first principles. As a result, neutrino scattering experiments such as MINERvA were conducted to provide data as input to reduce this uncertainty. This thesis presents a charged-current double-differential cross section measurement of electron neutrinos using the MINERvA detector in terms of available energy (a proxy of energy transfer), three-momentum transfer, and/or transverse momentum of the final state electron. This measurement focuses on the transition region between quasi-elastic and resonance processes, where the multi-nucleon knockout process dominates. The result is compared to a modified GENIE model and similar measurements using muon neutrino samples. In addition, this measurement reproduces the photon-like excess seen by previous MINERvA electron neutrino measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗