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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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

High-Fidelity Multiphysics Assessment of the Molten Chloride Reactor Experiment (MCRE) Integrating Neutronics, Thermal-hydraulics and Thermochemistry

This work presents a MOOSE-based Multiphysics model of the LOTUS MSR reactor system. The model includes the coarse-mesh turbulent thermal-hydraulics including passive advection of delayed neutron precursors of the primary system through Pronghorn, the power density and neutronics calculation employing Griffin, and the chemical interactions through Gibbs energy minimization and redox potential with Thermochimica. Incorporating a plate-out model, the full multi-physics model is used to evaluate the effects of deposition and removal of solid compounds formed in the molten salt in the reactor surfaces, evaluating the concentrations and regions in which nickel, chromium and iron would be deposited. Results indicate an almost isothermal state of the fuel during operation at 25 kW that do not increase the plate-out effects due to low temperature gradients.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2018

NLO QCD corrections to SM-EFT dilepton and electroweak Higgs boson production, matched to parton shower in POWHEG

Here, we discuss the Standard Model — Effective Field Theory (SM-EFT) contributions to neutral- and charge-current Drell-Yan production, associated production of the Higgs and a vector boson, and Higgs boson production via vector boson fusion. We consider all the dimension-six SM-EFT operators that contribute to these processes at leading order, include next-to-leading order QCD corrections, and interface them with parton showering and hadronization in Pythia8 according to the POWHEG method. We discuss existing constraints on the coefficients of dimension-six operators and identify differential and angular distributions that can differentiate between different effective operators, pointing to specific features of Beyond-the-Standard-Model physics.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2015

Semiclassical approach to heterogeneous vacuum decay

We derive the decay rate of an unstable phase of a quantum field theory in the presence of an impurity in the thin-wall approximation. This derivation is based on the how the impurity changes the (flat spacetime) geometry relative to case of pure false vacuum. Two examples are given that show how to estimate some of the additional parameters that enter into this heterogeneous decay rate. This formalism is then applied to the Higgs vacuum of the Standard Model (SM), where baryonic matter acts as an impurity in the electroweak Higgs vacuum. We find that the probability for heterogeneous vacuum decay to occur is suppressed with respect to the homogeneous case. That is to say, the conclusions drawn from the homogeneous case are not modified by the inclusion of baryonic matter in the calculation. On the other hand, we show that Beyond the Standard Model physics with a characteristic scale comparable to the scale that governs the homogeneous decay rate in the SM, can in principle lead to an enhanced decay rate.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

D0 same-charge dimuon asymmetry and possible new CP violation sources in the B{sub s}-B{sub s} system

Recently, the D0 Collaboration reported a large CP violation in the same-sign dimuon charge asymmetry which has the 3.2{sigma} deviation from the value estimated in the standard model. In this paper, several new physics models are considered: the minimal supersymmetric standard model, the two Higgs doublet model, the recent dodeca model, and a new Z{sup '} model. Generally, it is hard to achieve such a large CP violation consistently with other experimental constraints. We find that a scheme with extra nonanomalous U(1){sup '} gauge symmetry is barely consistent. In general, the extra Z{sup '} gauge boson induces the flavor changing neutral current interactions at tree level, which is the basic reason for allowing a large new physics CP violation. To preserve the U(1){sup '} symmetry at high energy, SU(2){sub L} singlet exotic heavy quarks of mass above 1 TeV and the standard model gauge singlet scalars are introduced.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

The interactive indoor-outdoor building energy modeling for enhancing the predictions of urban microclimates and building energy demands

There is a lack of an urban building energy modeling framework that considers the influence of surrounding buildings and local urban climate on building thermal performance. This can lead to inaccurate results since the thermal performance of individual buildings is heavily influenced by their surrounding built and climatic environment. This study establishes an interactive indoor-outdoor building energy modeling method to enhance the predictions of urban microclimates and building energy demands by coupling an urban physics model with a physics-based building energy model. Validation of the interactive coupling scheme uses field measurement datasets. Parametric simulation and analysis are conducted to understand the influence of the roof-to-canyon width ratio, canyon orientation, and ground vegetation fraction on canyon temperature, building energy consumption, and energy demand. Furthermore, the impacts of building energy model complexity (e.g., detailed vs. simplified building models) and coupling approaches on canyon temperature and building energy profiles are demonstrated using two case study buildings. In comparison with the one-way coupling approach, cooling energy consumption predicted with the dynamic two-way coupling approach varies by 3.5% and 0.5% for the detailed medium office building model and high-rise building model, respectively, and peak cooling demand varies by 8.4% and 7.0% for the detailed medium office building model and high-rise building model, respectively. Here this study also suggests that adopting a complex two-way coupling approach with environmental data exchange at various elevations is necessary for modeling tall buildings at the urban scale.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRSDate not supplied

Physics Informed Neural Nets for Systems Health Management

To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Development in data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. The research work presents application of physics-informed neural nets application to a representative electric powertrain for unmanned aerial vehicles. The model is composed of physics-derived and empirical equations, integrated with connected networks that are strategically placed within the model to substitute equations that are subject to large uncertainty. Polynomial fit driven by heuristics or empirical observations can be substituted by more flexible networks that can minimize the error between model predictions and observations without being restricted to a predefined functional form. This modeling strategy allows training of networks deep inside the model and unknown parameters in a single learning stage.

Physics Informed↗
DOE OSTI2022

Optimized Machine Learning Model for Predicting Groundwater Contamination

The use of physical models to predict groundwater contaminant movement remains technically challenging due to the complexity of the phenomena, the heterogeneity of key parameters in nature, and the presence of poorly defined interactive and feedback processes. New approaches to address these challenges are needed. In this study, we evaluate various Artificial Intelligence (AI)-based approaches to understand a hexavalent chromium (Cr(VI)) plumes located on the U.S. Department of Energy’s (DOE) Hanford Site in Richland, WA. The groundwater monitoring dataset used in this study included data from the 100 Area along the Columbia River and included data collected between 2010 to 2019. This study investigates the most prominent contaminant, Cr(VI), with the Extreme Gradient Boosting (XGBoost) machine learning model. The XGBoost models were compared with optimized versions using an Empirical Bayes Search Cross-Validation technique for better prediction. The optimized XGBoost model yielded an R^2 value of 0.99 on the training set and 0.85 on the testing set, whereas XGBoost without optimization yielded a value of 0.83 on the training set and 0.85 on the testing set. This paper provides an overview of a computational method for groundwater contamination modeling that shows promise for improving current remediation efforts.

Mazumdar, Hirak↗
DOE OSTI2012

Boreal lakes moderate seasonal and diurnal temperature variation and perturb atmospheric circulation: Analyses in the Community Earth System Model 1 (CESM1)

We used a lake thermal physics model recently coupled into the Community Earth System Model 1 (CESM1) to study the effects of lake distribution in present and future climate. Under present climate, correcting the large underestimation of lake area in CESM1 (denoted CCSM4 in the configuration used here) caused 1 °C spring decreases and fall increases in surface air temperature throughout large areas of Canada and the US. Simulated summer surface diurnal air temperature range decreased by up to 4 °C, reducing CCSM4 biases. These changes were much larger than those resulting from prescribed lake disappearance in some present-day permafrost regions under doubled-CO 2 conditions. Correcting the underestimation of lake area in present climate caused widespread high-latitude summer cooling at 850 hPa. Significant remote changes included decreases in the strength of fall Southern Ocean westerlies. We found significantly different winter responses when separately analysing 45-yr subperiods, indicating that relatively long simulations are required to discern the impacts of surface changes on remote conditions. We also investigated the surface forcing of lakes using idealised aqua-planet experiments which showed that surface changes of 2 °C in the Northern Hemisphere extra-tropics could cause substantial changes in precipitation and winds in the tropics and Southern Hemisphere. Shifts in the Inter-Tropical Convergence Zone were opposite in sign to those predicted by some previous studies. Zonal mean circulation changes were consistent in character but much larger than those occurring in the lake distribution experiments, due to the larger magnitude and more uniform surface forcing in the idealised aqua-planet experiments.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2007

A Shock-Refracted Acoustic Wave Model for Screech Amplitude in Supersonic Jets

A physical model is proposed for the estimation of the screech amplitude in underexpanded supersonic jets. The model is based on the hypothesis that the interaction of a plane acoustic wave with stationary shock waves provides amplification of the transmitted acoustic wave upon traversing the shock. Powell's discrete source model for screech incorporating a stationary array of acoustic monopoles is extended to accommodate variable source strength. The proposed model reveals that the acoustic sources are of increasing strength with downstream distance. It is shown that the screech amplitude increases with the fully expanded jet Mach number. Comparisons of predicted screech amplitude with available test data show satisfactory agreement. The effect of variable source strength on the directivity of the fundamental (first harmonic, lowest frequency mode) and the second harmonic (overtone) is found to be unimportant with regard to the principal lobe (main or major lobe) of considerable relative strength, and is appreciable only in the secondary or minor lobes (of relatively weaker strength).

Kandula, Max↗
DOE OSTI2022

Cabana: A Performance Portable Library for Particle-Based Simulations

Particle-based simulations are ubiquitous throughout many fields of computational science and engineering, spanning the atomistic level with molecular dynamics (MD), to mesoscale particle-in-cell (PIC) simulations for solid mechanics, device-scale modeling with PIC methods for plasma physics, and massive N-body cosmology simulations of galaxy structures, with many other methods in between (Hockney & Eastwood, 1989). While these methods use particles to represent significantly different entities with completely different physical models, many low-level details are shared including performant algorithms for short- and/or long-range particle interactions, multi-node particle communication patterns, and other data management tasks such as particle sorting and neighbor list construction. Cabana is a performance portable library for particle-based simulations, developed as part of the Co-Design Center for Particle Applications (CoPA) within the Exascale Computing Project (ECP) (Alexander et al., 2020). The CoPA project and its full development scope, including ECP partner applications, algorithm development, and similar software libraries for quantum MD, is described in (Mniszewski et al., 2021). Cabana uses the Kokkos library for on-node parallelism (Edwards et al., 2014; Trott et al., 2022), enabling simulation on multi-core CPU and GPU architectures, and MPI for GPU-aware, multi-node communication. Cabana provides particle simulation capabilities on almost all current Kokkos backends, including serial execution, OpenMP (including OpenMP-Target for GPUs), CUDA (NVIDIA GPUs), HIP (AMD GPUs), and SYCL (Intel GPUs), providing a clear path for the coming generation of accelerator-based exascale hardware. Cabana builds on Kokkos by providing new particle data structures and particle algorithms resulting in a similar execution policy-based, node-level programming model that is intended to be used in addition to the core Kokkos library within an application. Cabana is designed as an application and physics agnostic, but particle-specific toolkit which can either be used to generate a new application, or to be used as needed in existing applications at various levels of invasiveness including through interfaces that wrap user memory in existing data structures.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2008

A Multi-Scale Modeling System with Unified Physics

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. In recent years, exponentially increasing computer power has extended cloud-resolving-mode1 integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique.

Tao, Wei-Kuo↗
DOE OSTI2025

Learning Physically Interpretable Atmospheric Models From Data With WSINDy

The multiscale and turbulent nature of Earth's atmosphere has historically rendered accurate weather modeling a hard problem. Recently, there has been an explosion of interest surrounding data-driven approaches to weather modeling, which in many cases show improved forecasting accuracy and computational efficiency when compared to traditional methods. However, many of the current data-driven approaches employ highly parameterized neural networks, often resulting in uninterpretable models and limited gains in scientific understanding. In this work, we address the interpretability problem by explicitly discovering partial differential equations governing atmospheric phenomena, identifying symbolic mathematical models with direct physical interpretations. The purpose of this paper is to demonstrate that, in particular, the weak-form sparse identification of nonlinear dynamics (WSINDy) algorithm can learn effective atmospheric models from both simulated and assimilated data. Our approach adapts the standard WSINDy algorithm to work with high-dimensional fluid data of arbitrary spatial dimension.

58 GEOSCIENCES↗
DOE OSTI2014

Center for Theoretical Underground Physics and Related Areas - CETUP*2013 Summer Program

In response to an increasing interest in experiments conducted at deep underground facilities around the world, in 2010 the theory community has proposed a new initiative - a Center for Theoretical Underground Physics and Related Areas (CETUP*). The main goal of CETUP* is to bring together people with different talents and skills to address the most exciting questions in particle and nuclear physics, astrophysics, geosciences, and geomicrobiology. Scientists invited to participate in the program do not only provide theoretical support to the underground science, they also examine underlying universal questions of the 21 st century including: What is dark matter?, What are the masses of neutrinos?, How have neutrinos shaped the evolution of the universe?, How were the elements from iron to uranium made?, What is the origin and thermal history of the Earth? The mission of the CETUP* is to promote an organized research in physics, astrophysics, geoscience, geomicrobiology and other fields related to the underground science via individual and collaborative research in dynamic atmosphere of intense scientific interactions. Our main goal is to bring together scientists scattered around the world, promote the deep underground science and provide a stimulating environment for creative thinking and open communication between researches of varying ages and nationalities. CETUP*2014 included 5 week long program (June 24 – July 26, 2013) covering various theoretical and experimental aspects of Dark Matter, Neutrino Physics and Astrophysics. Two week long session focused on Dark Matter (June 24-July 6) was followed by two week long program on Neutrino Physics and Astrophysics (July 15-26). The VII th International Conference on Interconnections between Particle Physics and Cosmology (PPC) was sandwiched between these sessions (July 8-13) covering the subjects of dark matter, neutrino physics, gravitational waves, collider physics and other from both theoretical end experimental aspects. PPC was initiated at Texas A&M University in 2007 and travelled to many places which include Geneva, Turin, Seoul (S. Korea) etc. during the last 5 years before coming back to USA. The objectives of CETUP* and PPC were to analyze the connection between dark matter and particle physics models, discuss the connections among dark matter, grand unification models and recent neutrino results and predictions for possible experiments, develop a theoretical understanding of the three-neutrino oscillation parameters, provide a stimulating venue for exchange of scientific ideas among experts in neutrino physics and unification, connect with venues for public education outreach to communicate the importance of dark matter, neutrino research, and support of investment in science education, support mission of the Snowmass meeting and allow for extensive discussions of the ideas crucial for the future of high energy physics. The selected subjects represented the forefront of research topics in particle and nuclear physics, for example: recent precise measurements of all the neutrino mixing angles (that necessitate a theoretical roadmap for future experiments) or understanding of the nature of dark matter (that allows us to comprehend the composition of the cosmos better). All the covered topics are considered as a base for new physics beyond the Standard Model of particle physics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2007

A Risk-Based Approach for Aerothermal/TPS Analysis and Testing

The current status of aerothermal and thermal protection system modeling for civilian entry missions is reviewed. For most such missions, the accuracy of our simulations is limited not by the tools and processes currently employed, but rather by reducible deficiencies in the underlying physical models. Improving the accuracy of and reducing the uncertainties in these models will enable a greater understanding of the system level impacts of a particular thermal protection system and of the system operation and risk over the operational life of the system. A strategic plan will be laid out by which key modeling deficiencies can be identified via mission-specific gap analysis. Once these gaps have been identified, the driving component uncertainties are determined via sensitivity analyses. A Monte-Carlo based methodology is presented for physics-based probabilistic uncertainty analysis of aerothermodynamics and thermal protection system material response modeling. These data are then used to advocate for and plan focused testing aimed at reducing key uncertainties. The results of these tests are used to validate or modify existing physical models. Concurrently, a testing methodology is outlined for thermal protection materials. The proposed approach is based on using the results of uncertainty/sensitivity analyses discussed above to tailor ground testing so as to best identify and quantify system performance and risk drivers. A key component of this testing is understanding the relationship between the test and flight environments. No existing ground test facility can simultaneously replicate all aspects of the flight environment, and therefore good models for traceability to flight are critical to ensure a low risk, high reliability thermal protection system design. Finally, the role of flight testing in the overall thermal protection system development strategy is discussed.

Wright, Michael J.↗
DOE OSTI2022

Closing the loop between microstructure and charge transport in conjugated polymers by combining microscopy and simulation

A grand challenge in materials science is to identify the impact of molecular composition and structure across a range of length scales on macroscopic properties. We demonstrate a unified experimental–theoretical framework that coordinates experimental measurements of mesoscale structure with molecular-level physical modeling to bridge multiple scales of physical behavior. Here we apply this framework to understand charge transport in a semiconducting polymer. Spatially-resolved nanodiffraction in a transmission electron microscope is combined with a self-consistent framework of the polymer chain statistics to yield a detailed picture of the polymer microstructure ranging from the molecular to device relevant scale. Using these data as inputs for charge transport calculations, the combined multiscale approach highlights the underrepresented role of defects in existing transport models. Short-range transport is shown to be more chaotic than is often pictured, with the drift velocity accounting for a small portion of overall charge motion. Local transport is sensitive to the alignment and geometry of polymer chains. At longer length scales, large domains and gradual grain boundaries funnel charges preferentially to certain regions, creating inhomogeneous charge distributions. While alignment generally improves mobility, these funneling effects negatively impact mobility. The microstructure is modified in silico to explore possible design rules, showing chain stiffness and alignment to be beneficial while local homogeneity has no positive effect. This combined approach creates a flexible and extensible pipeline for analyzing multiscale functional properties and a general strategy for extending the accesible length scales of experimental and theoretical probes by harnessing their combined strengths.

42 ENGINEERING↗
DOE OSTI2023

Data-driven modeling and control of an X-ray bimorph adaptive mirror

Adaptive X-ray mirrors are being adopted on high-coherent-flux synchrotron and X-ray free-electron laser beamlines where dynamic phase control and aberration compensation are necessary to preserve wavefront quality from source to sample, yet challenging to achieve. Additional difficulties arise from the inability to continuously probe the wavefront in this context, which demands methods of control that require little to no feedback. In this work, a data-driven approach to the control of adaptive X-ray optics with piezo-bimorph actuators is demonstrated. This approach approximates the non-linear system dynamics with a discrete-time model using random mirror shapes and interferometric measurements as training data. For mirrors of this type, prior states and voltage inputs affect the shape-change trajectory, and therefore must be included in the model. Without the need for assumed physical models of the mirror's behavior, the generality of the neural network structure accommodates drift, creep and hysteresis, and enables a control algorithm that achieves shape control and stability below 2 nm RMS. Using a prototype mirror and ex situ metrology, it is shown that the accuracy of our trained model enables open-loop shape control across a diverse set of states and that the control algorithm achieves shape error magnitudes that fall within diffraction-limited performance.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Tidal Love numbers of novel and admixed celestial objects

A sub-fraction of dark matter or new particles trapped inside celestial objects can significantly alter their macroscopic properties. Here, we investigate the new physics imprint on celestial objects by using a generic framework to solve the Tolman-Oppenheimer-Volkoff (TOV) equations for up to two fluids. We test the impact of populations of new particles on celestial objects, including the sensitivity to self-interaction sizes, new particle mass, and net population mass. Applying our setup to neutron stars and boson stars, we find rich phenomenology for a range of these parameters, including the creation of extended atmospheres. These atmospheres are detectable by their impact on the tidal love number, which can be measured at upcoming gravitational wave experiments such as Advanced LIGO, the Einstein Telescope, and LISA. We release our calculation framework as a publicly available code at this URL, allowing the TOV equations to be generically solved for arbitrary new physics models in novel and admixed celestial objects.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗