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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Validation of the HyRAM+ physics models for use with propane

The Hydrogen Risk Assessment Model Plus (HyRAM+) toolkit combines quantitative risk assessment with simulations of unignited dispersion, ignited turbulent diffusion flames, and indoor accumulation with delayed ignition of fuels. HyRAM+ is differentiated from HyRAM in that it includes models and leak data for other alternate fuels. The models of the physical phenomena need to be validated for each of the fuels in the toolkit. This report shows the validation for propane which is being used as a surrogate for autogas, which is a mixture of propane and butane and used in internal combustion engines in vehicles. For flame length comparisons, five previously published experiments from peer reviewed journals were used to validate our models. The validation looked at flame lengths and flame widths with respect to different leak diameters, mass flow rates, and source pressures. Most of the sources included more than one set of experimental data, which were collected using different methods (CCD cameras, IR visualization etc.). In general, HyRAM+ overpredicts the flame lengths by around 65%. For heat and radiation models, we compared the heat flux and radiation data reported from two different sources to the values calculated by HyRAM+. For higher mass flow rates, the HyRAM+ calculated flame length results gave a better estimate of what is found in the experiments (65% error), but a higher error (85%) is observed between the HyRAM+ calculated lengths and the experimental flame lengthsfor lower mass flows. Some differences can be attributed to outdoor environmental effects (i.e. wind speed) and uncertainties in jet flame shapes. The propane flame trajectory is predicted for a high Reynolds number case with Re = 12,500 and a low Reynolds number case where Re = 2,000. The Re=12,500 case which is momentum dominated matches well with the experimental flame trajectory, but the agreement for the bouancy driven low Reynolds number case is not as good. Dispersion modeling for unignited propane was also analyzed. We compared the mole fraction, mixture fraction, mean velocity, concentration half width, and inverse mass concentration over an axial distance from different credible journals to the values calculated by HyRAM+. The results display good agreement but generally, HyRAM+ predicts a wider profile for mole fraction and mixture fraction experiments. Overall, HyRAM+’s results are reasonable for predicting the flame length, heat flux, flame trajectory, and dispersion for propane and can be used in risk analyses

08 HYDROGEN↗
NASA NTRS1990

A physical model for the acousto-ultrasonic method

A basic physical explanation, a model, and comments on NDE application of the acousto-ultrasonic (AU) method for composite materials are presented. The basis of this work is a set of experiments where a sending and a receiving piezoelectric transducer were both oriented normal to the surface, at different points, on aluminum plates, various composite plates, and a tapered aluminum plate. The purpose and basic idea is introduced. Also, general comments on the AU method are offered. A literature review is offered for areas pertinent, such as composite materials, wave propagation, ultrasonics, and the AU. Special emphasis is given to theory which is used later on and past experimental results that are important to the physical understanding of the AU method. The experimental set-up, procedure, and the ensuing analysis are described. The experimental results are presented in both a quantitative and qualitative manner. A physical understanding of experimental results based on elasticity solution is furnished. Modeling and applications of the AU method is discussed for composite material and general conclusions are stated. The physical model of the AU method for composite materials is offered, something which has been much needed and sorely lacking. This physical understanding is possible due to the extensive set of experimental measurements, also reported.

Kiernan, Michael T.↗
DOE OSTI2026

Search for Beyond the Standard Model physics with anomaly detection in multilepton final states in pp collisions at s=13TeV with the ATLAS detector

A model-agnostic search for Beyond the Standard Model physics is presented, targeting final states with at least four light leptons (electrons or muons). The search regions are separated by event topology and unsupervised machine learning is used to identify anomalous events in the full 140 fb-1$$^{-1}$$ of proton–proton collision data collected with the ATLAS detector during Run 2. No significant excess above the Standard Model background expectation is observed. Model-agnostic limits are presented in each topology, along with limits on several benchmark models including vector-like leptons, wino-like charginos and neutralinos, or smuons. Limits are set on the flavourful vector-like lepton model for the first time.

Aad, G↗
DOE OSTI2020

Revealing transient powder-gas interaction in laser powder bed fusion process through multi-physics modeling and high-speed synchrotron x-ray imaging

Laser powder bed fusion (LPBF) is an emerging metal additive manufacturing process. The gas-driven powder motions in laser powder bed fusion have significant influence on the build quality. However, the transient powder-gas interaction has not been well understood due to the challenges in quantitative experiment measurements. In this work, the powder-gas interaction for a single pulse laser illuminating on the powder bed is studied. We establish a multi-physics model to simulate the complex liquid/gas flow as well as the gas-driven powder motions, which is substantiated by high-speed synchrotron x-ray imaging. We identify and quantify four characteristic modes of powder-gas interaction in LPBF. The motion of a powder is controlled by one or multiple interaction modes collectively. As revealed by simulations and confirmed by experiments, powders can merge into the molten pool from its rim, be ejected at different divergence angles (powder spattering), or dive into the molten pool to cause significant molten pool fluctuation. Overall, our results provide insights toward the driving forces controlling the dynamic powder behavior, which pave the way for reducing structure defects during the build process.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Multi-physics modeling of tungsten collector probe samples during the WEST C4 He campaign

Abstract We describe the results of a multi-scale, multi-physics modeling assessment of SOLPS-ITER, hPIC2, RustBCA and Xolotl, in which five single-crystal tungsten (W) samples were placed in a reciprocating collector probe and exposed to helium (He) plasma in the WEST fusion device. In our models, we considered a pure (100 %) He plasma, as well as one with oxygen (O) present (95% He 5% O) corresponding to the impurity concentration estimated during the C4 He campaign in WEST. Our SOLPS simulations approximately match experimental reciprocating Langmuir probe plasma measurements of plasma density and temperature. Using these plasma parameters as input, hPIC2 and RustBCA predict that the presence of oxygen impurities lead to a 15%–20% decrease in ion and heat fluxes to the surface, and an order of magnitude higher sputtering yields (compared with a pure He plasma). Xolotl predictions for the response of tungsten to plasma surface interactions (PSIs) agree with experimental LAMS analysis, and indicate large near-surface He concentrations, which quickly decay with depth. Our model also shows an increasing role of erosion—in removing the near-surface He—with time. Overall, slightly higher retention is predicted for tungsten exposed to a pure He plasma, with the largest differences in the near-surface gas content caused by the large oxygen-induced erosion. This highlights the important role that impurities play in PSI. Therefore, future work will focus on providing a fully self-consistent description of oxygen (and oxides, etc.) in our models, through multi-species implementation in GITR and inclusion of oxygen and tungsten oxide formation in Xolotl.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1987

The use of molten salts as physical models for the study of solidification in metals and semiconductors

It is presently noted that molten salts possess attributes rendering them attractive as physical models of cast metals in solidification studies. Molten alkali halides have an approximately correct Prandtl number for this modeling of metallic melts, and are transparent to visible light. Attention is given to solidification in the LiCl-KCl system, in order to determine whether such phenomena as solute rejection can be observed and characterized through the application of laser schlieren imaging.

Koziol, Jurek K.↗
NASA NTRS1977

A simple physical model for X-ray burst sources

In connection with information considered by Illarianov and Sunyaev (1975) and van den Heuvel (1975), a simple physical model for an X-ray burst source in the galactic disk is proposed. The model includes an unevolved OB star with a relatively weak stellar wind and a compact object in a close binary system. For some reason, the stellar wind from the OB star is unable to accrete steadily on to the compact object. When the stellar wind is sufficiently weak, the compact object accretes irregularly, leading to X-ray bursts.

Joss, P. C.↗
DOE OSTI2021

Development of a Multi-physics Model to Optimize Continuous Liquid Interface Production (CLIP) for Additive Manufacturing (Carbon3D HPC4Mfg Final Report)

Continuous Liquid Interface Production (CLIP) is poised to bring additive manufacturing to multiple American manufacturing sectors owing to its unique combination of rapid print speeds and material options that resemble injection molding thermoplastics. In spite of these benefits, CLIP is still a maturing process. To improve our understanding and control of the process, this project developed a multi-physics computational model that encompasses the coupled chemical-physical processes of photopolymerization and fluid flow to predict part outcomes. A physically predictive model can enable rapid optimization of CLIP and reduce the current cycle time and waste associated with optimization by four-fold. Ultimately, this effort will help open the U.S. $400B plastic manufacturing industry to the key benefits of additive manufacturing, namely mass customization, unlimited design space, and a cost- and energy-effective path to mainstream manufacturing. In the course of the project we produced a model which coupled fluid-flow, species transport, and photochemistry to model the Carbon CLIP process. As the development proceeded, we validated the code against theory and experiments. The resulting code was transferred to Carbon, and we expect it to be a useful part of their modeling capability. Future work includes improvements to the fluid solver’s robustness and performance, along with the addition of additional physics models.

36 MATERIALS SCIENCE↗
NASA NTRS1989

Conservation equations and physical models for hypersonic air flows in thermal and chemical nonequilibrium

The conservation equations for simulating hypersonic flows in thermal and chemical nonequilibrium and details of the associated physical models are presented. These details include the curve fits used for defining thermodynamic properties of the 11 species air model, curve fits for collision cross sections, expressions for transport properties, the chemical kinetics models, and the vibrational and electronic energy relaxation models. The expressions are formulated in the context of either a two or three temperature model. Greater emphasis is placed on the two temperature model in which it is assumed that the translational and rotational energy models are in equilibrium at the translational temperature, T, and the vibrational, electronic, and electron translational energy modes are in equilibrium at the vibrational temperature, T sub v. The eigenvalues and eigenvectors associated with the Jacobian of the flux vector are also presented in order to accommodate the upwind based numerical solutions of the complete equation set.

Peter A. Gnoffo↗
NASA NTRS1993

A physical model of the infrared-to-radio correlation in galaxies

We explore the implications of the IR-radio correlation in star-forming galaxies, using a simple physical model constrained by the constant global ratio q of IR to radio emission and by the radial falloff of this ratio in disks of galaxies. The modeling takes into account the diffusion, radiative decay, and escape of cosmic-ray electrons responsible for the synchrotron emission, and the full range of optical depths to dust-heating photons. We introduce two assumptions: that dust-heating photons and radio-emitting cosmic-ray electrons are created in constant proportion to each other as part of the star formation activity, and that gas and magnetic field are well coupled locally, expressed as B proportional to n exp beta, with beta between 1/3 and 2/3. We conclude that disk galaxies would maintain the observed constant ratio q under these assumptions if the disk scale height h(0) and the escape scale length l(esc) for cosmic-ray electrons followed a relation of the form l(esc) proportional to h(0) exp 1/2; the IR-to-radio ratio will then depend very weakly on interstellar density, and, therefore, on magnetic field strength or mean optical depth.

Helou, G.↗
DOE OSTI2022

Basic elements for simulations of standard-model physics with quantum annealers: Multigrid and clock states

Here, we explore the potential of D-Wave's quantum annealers for computing some of the basic components required for quantum simulations of standard model physics. By implementing a basic multigrid (including “zooming”) and specializing Feynman-clock algorithms, D-Wave's Advantage is used to study harmonic and anharmonic oscillators relevant for lattice scalar field theories and effective field theories, the time evolution of a single plaquette of SU(3) Yang-Mills lattice gauge field theory, and the dynamics of flavor entanglement in four-neutrino systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Deep Reinforcement Learning Enabled Physical-Model-Free Two-Timescale Voltage Control Method for Active Distribution Systems

Active distribution networks are being challenged by frequent and rapid voltage violations due to renewable energy integration. Conventional model-based voltage control methods rely on accurate parameters of the distribution networks, which are difficult to achieve in practice. This paper proposes a novel physical-model-free two-timescale voltage control framework for active distribution systems. To achieve fast control of PV inverters, the whole network is first partitioned into several subnetworks using voltage-reactive power sensitivity. Then, the scheduling of PV inverters in the multiple sub-networks is formulated as Markov games and solved by a multi-agent soft actor-critic (MASAC) algorithm, where each subnetwork is modeled as an intelligent agent. All agents are trained in a centralized manner to learn a coordinated strategy while being executed based on only local information for fast response. For the slower time-scale control, OLTCs and switched capacitors are coordinated by a single agent-based SAC algorithm using the global information with considering control behaviors of the inverters. Particularly, the two-level agents are trained concurrently with information exchange according to the reward signal calculated from the data-driven surrogate model. Comparative tests with different benchmark methods on IEEE 33-and 123-bus systems and 342-node low voltage distribution system demonstrate that the proposed method can effectively mitigate the fast voltage violations and achieve systematical coordination of different voltage regulation assets without the knowledge of accurate system model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Defensive Cybersecurity Architecture Design Using Force-on-Force Cyber-Physical Modeling

Currently, nuclear power plant physical security systems are highly dependent on air-gaps as a protective measure against cyber-threats. Cyber-physical threats become more likely as advanced cyber-threat capabilities to jump air-gaps transition into common use. Defending against the emerging threat of cyber-enabled physical intrusions is poorly understood. The consequence of these cyber-physical attacks has no quantitative analysis method to inform risk-informed, performance-based cybersecurity approaches. By modifying the physical security simulation tool Dante, cyber-physical threat consequence was able to be analyzed on a notional facility. The results of this analysis are used to design a Defensive Cybersecurity Architecture (DCSA) for the physical security system to produce example resilience measures for this notional facility. A DCSA defines security levels to provide a graded approach for defending plant functions, and security zones for trusted communication between systems. This approach can be applied to real world systems to produce physical protection systems and response measures that are resilient to cyber-physical threats.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2025

Physical models reveal indirect reader protein interactions that facilitate epigenetic crosstalk

The spatial organization of chromatin is governed by epigenetic factors, including epigenetic marks and the reader proteins that bind them. By dictating the accessibility of genomic loci, epigenetic factors contribute to the physical regulation of gene expression, enabling diverse cellular phenotypes to be encoded by a shared genome in an individual. Epigenetic dysregulation can lead to aberrations in chromatin architecture, contributing to diseases such as neurological disorders and cancers. Despite the known importance of chromatin organization for human health, the physical mechanisms governing chromatin folding remain underspecified. In this work, we develop a physical model of chromatin organization based on contributions from multiple epigenetic factors. Using our model, we evaluate how conditions in the nuclear environment and crosstalk between epigenetic marks affect the compartmentalization of chromatin into dense heterochromatin and loose euchromatin. Our results emphasize the role of reader protein binding in chromatin compartmentalization. We show that reader proteins interact through an indirect mechanism facilitated by the shared chromatin “scaffold” to which they bind. Under a scenario where reader proteins compete for binding sites, we find that indirect interactions affect the program adopted by the chromatin fiber. By isolating indirect modes of epigenetic crosstalk, we demonstrate how the interplay between epigenetic patterning and environmental factors influences chromatin architecture.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2021

A Physical Model for a Slim Convective Dusty Disk in AGN

An accretion disk in an Active Galactic Nucleus (AGN) harbors and shields dust from external illumination. Our model shows that at the mid-plane of the disk around a MBH = 107M black hole, dust can exist at 0:1pc from the black hole, compared to 0.5pc outside of the disk where such self-shielding is constrained. We construct a physical model of a disk region approximately located between the radius of dust sublimation at the disk mid-plane and the radius at which dust sublimes at the disk surface. Our main conclusion is that for a wide range of model parameters such as local accretion rate and/or opacity, the accretion disk’s own radiation pressure on dust significantly influences its vertical structure. In this region convection plays important role in the vertical transport of energy. When the local accretion rate exceeds 2:5M yr the 10􀀀2pc-scale disk is super-critical with respect to dust opacity. Such a disk puffs up and transforms from geometrically thin to slim. Our model fits into the narrative of a "failed wind" scenario of Czerny & Hryniewicz (2011) and the "compact torus" model of Baskin & Laor (2018), incorporating them as variations of the radiative dusty disk model.

A Dorodnitsyn↗
NASA NTRS2020

A Physical Model of Moulin Evolution on the Greenland Ice Sheet

Nearly all proglacial water discharge from the Greenland Ice Sheet is routed englacially via moulins. Identification of these moulins in high-resolution imagery is a frequent topic of study, but the processes controlling how and where moulins form remain poorly understood. Because moulins may reasonably compose approximately 10-15% of the englacial-subglacial hydrologic system, the evolution and shape of moulins can alter both the timing and variability of meltwater inputs to the bed. This evolution can impact both the form of the subglacial hydrologic system and associated response of ice motion. Here, we develop a physical model of moulin formation and evolution to constrain the role of englacial processes in shaping the form and structure of the subglacial hydrologic system. Within this model, moulin geometry is controlled by a balance of viscous and elastic deformation and is dependent on that deformation, refreezing, and the dissipation of turbulent and sensible heat energy. All of which are dependent on the characteristics of the available supraglacial meltwater and the surrounding ice. We find moulin geometry is responsive to changes in these parameters over the course of hours to days, indicating that diurnal and multi-day variations in melt can substantially alter the geometry of a moulin and, consequently, the pressure-discharge relationship at the bed of the ice sheet. Therefore, there is no single moulin shape that can appropriately represent englacial storage across the Greenland Ice Sheet.

Andrews, Lauren C.↗
NASA NTRS2019

A Physical Model of Moulin Formation and Evolution

Nearly all proglacial water discharge from the present-day Greenland Ice Sheet is routed englacially via moulins. Identification of these moulins in high-resolution imagery is a frequent topic of study, but the processes controlling how and where moulins form, including on past ice sheets for which remote-sensing data are not available, remain poorly understood. Because moulins may reasonably compose approximately 10-15% of the englacial-subglacial hydrologic system, the evolution and shape of moulins can alter the timing of meltwater inputs to the bed. This evolution can impact both the form of the subglacial hydrologic system and the structure of associated geomorphological structures. Here, we develop a physical model of moulin formation and evolution to constrain the role of englacial processes in controlling the form and structure of the subglacial hydrologic system. Ice deformation within and around a moulin is both viscous and elastic, with the rate of turbulent and heat dissipation from water circulation in the moulin controlling both moulin wall melting and warming of the surrounding ice. We find moulin geometry is responsive to changes in these parameters over hours to days, indicating that diurnal and multi-day variations in surface melt can substantially alter the geometry of a moulin and the pressure-discharge relationship at the bed of the ice sheet. These results should be considered carefully when determining surface water inputs for subglacial hydrologic models. In the future, a parameter space study of these results will be combined with an analytic model to create a predictive, stochastic model of moulin and crevasse locations. This future model will be applicable to constraining the potential for surface-to-bed connections in regions where the exact ice-sheet surface morphology is not known, including ice sheets under future warming atmospheric conditions, and paleo ice sheets, where moulins created modern landforms.

Andrews, Lauren C.↗
DOE OSTI2026

Battery Life Prediction Using Reduced-Order Physics Models and Machine Learning (CRADA Final Report)

Phase 1 (Original CRADA, plus no-cost extension modifications #1-3, 6/1/2017 to 3/13/2021): The Australian Department of Defence (AUDoD) is performing accelerated aging tests of Li-ion batteries to benchmark their reliability and degradation characteristics. Using its previously developed battery lifetime predictive model framework, the National Laboratory of the Rockies (NLR) will develop analytical models based the AUDoD data to predict lifetime of the multiple Li-ion battery chemistries under real-world use scenarios of interest to AUDoD. The NLR model is based on physical degradation mechanisms encountered by Li-ion batteries and has been previously validated. Phase 2 (CRADA modification #4, plus no-cost extension modification #5, 2/22/2021 to 3/30/2025): Train and support Australian Department of Defence personnel to use NLR software for model-based estimation of Li-ion battery lifetime using accelerated battery aging data collected by the Australian Department of Defence. Under separate DOE funding from 2019 to 2021, NLR enhanced its battery life-prediction software using machine learning algorithms to automate portions of the model-fitting process, requiring significantly less labor and expert judgment and also adding uncertainty quantification, increasing statistical rigor. Under Phase 2, NLR will customize NLR Software and provide it to AuDoD. NLR will enhance its NLR Model to capture aging modes of AuDoD's multi-cell modules, including cell-balancing effects. NLR will develop example single-cell and multi-cell models based on one AuDoD battery aging dataset. NLR will train AuDoD personnel on NLR Software. By the conclusion of the project, NLR will have provided AuDoD the training materials, a user manual and software needed to perform their own analysis of additional and/or future battery aging datasets.

33 ADVANCED PROPULSION SYSTEMS↗