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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

Rapid Construction of Validated Chemistry Models for Advanced Biofuels (Co-Optima Final Report)

Computer methods were developed and demonstrated that make it possible to predict the combustion and pyrolysis chemistry of proposed biofuels, even before the biofuels are ever manufactured or experimentally tested. The methods are based on first-principles calculations of reaction rates and equilibria. A large number of complicated calculations are required, so we developed a computer workflow that automates many of the steps. With the chemical structure of the biofuel and the system conditions (temperature, pressure, compositions, etc.) as the input, the computer methods can construct a detailed kinetic model with refined parameters without intense human intervention. The automation of model construction makes it practical for a single engineer to make the predictions in a reasonable time period. The accuracy of the computer predictions was tested by measuring the time-profiles of various reaction intermediates (carbon monoxide, carbon dioxide, water, formaldehyde, methane, and ethylene) formed as the biofuels pyrolyze or ignite using sophisticated laser shock tube methods. Several biofuels, including methyl propyl ether, cyclopentanone, butyl acetate isomers, etc., were carefully studied to demonstrate the validity of the proposed computational and experimental methodology. This research project opens up the possibility for assessing some proposed biofuels on the computer without expensive experimental campaigns. The new computer methods are open source and well-documented, allowing a knowledgeable modeler to easily access the developed methods and implement them in their work routine. Moreover, they are also convenient and powerful, promising for developing the fuel chemistry models needed for use in engine simulators, facilitating co-optimization of new engine designs with new fuels.

09 BIOMASS FUELS↗
DOE OSTI2024

Concrete Thermal Energy Storage Enabling Flexible Operation without Coal Plant Cycling

The work described in this report is responsive to the Office of Fossil Energy program “Energy Storage for Fossil Power Generation.” The pilot plant built as a result of this project demonstrated the feasibility and performance of a concrete thermal energy storage (CTES) system integrated with a supercritical coal power plant. The 10 MWh electrical (>25 MWh thermal) CTES unit, developed by Storworks Power, was designed to enable flexible operation of coal plants without cycling damage. The project's key technical achievements showcase a significant advancement in energy storage technology. A modular CTES system using 42 “Bolderblocs” units was successfully designed and constructed at Alabama Power’s Plant Gaston Unit 5, with each block containing embedded stainless-steel coils in specialized, cost-effective high-temperature concrete. The system interfaced seamlessly with the plant's 3500 psig (241 barg), 1000°F (538°C) supercritical steam, demonstrating operational flexibility. Over 86 full cycles, the CTES exhibited rapid charging and discharging capabilities, effectively mimicking steam turbine feed conditions and handling varying load profiles and storage durations. Performance validation confirmed the system's ability to consistently meet design target steam conditions of 75 bar-a and ~400°C for nominal baseline discharge. The concrete material withstood repeated thermal cycling without degradation, validating earlier lab-scale tests. Integration of balance of plant components, including a condensate management system with storage tank and air-cooled condenser, minimized plant interfaces and water consumption. A robust control scheme ensured safe, automated operation across various scenarios. Key learnings from the project were invaluable: 1. Initial concrete drying and commissioning procedures were refined for future deployments, enhancing efficiency in subsequent installations. 2. System flexibility exceeded expectations, with rapid response to changing conditions. 3. Design improvements were identified including optimized insulation and piping that will enhance overall system efficiency in future deployments 4. Full cycle thermal roundtrip efficiencies exceeded 88%. While the roundtrip electrical efficiency was somewhat limited by known challenges using input steam, such constraints may be mitigated by swapping steam for hot air as thermal input. 5. A summary of key performance parameters for the pilot test and predicted performance of a full scale commercial system with specified improvements determined from the pilot are shown in Section 8. The project faced challenges, including COVID-19 delays and host plant availability constraints. However, these were overcome through adaptive planning and execution. The successful management of these obstacles demonstrated the resilience and adaptability of the project team and the robustness of the CTES technology. This successful pilot demonstrates the potential for CTES to enhance coal plant flexibility, supporting grid stability as renewable penetration increases. The validated design and operational data provide a solid foundation for scaling up to utility-scale implementations, potentially transforming how thermal plants operate in evolving energy landscapes. The system's ability to rapidly respond to changing grid conditions while maintaining high efficiency makes it a promising solution for balancing intermittent renewable energy sources. Furthermore, the project highlighted the potential for even greater efficiencies in future iterations. The use of air as an input medium could potentially eliminate the limitations observed with steam input, opening new possibilities for energy storage applications beyond coal plant integration. In conclusion, this pilot project not only achieved its primary goals but also uncovered additional benefits and potential applications of the CTES technology. It represents a significant step forward in addressing the challenges of grid stability and flexibility in an increasingly renewable-driven energy landscape.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Frozen Freedom: Unleashing Grocery Store Demand Flexibility: Preprint

Grocery stores consumed approximately 3% of total electricity used by commercial buildings in the U.S. in 2018 (EIA 2018), representing a unique end-use load profile characterized by the critical use of refrigerated display cases. Exploring demand response (DR) scenarios in grocery stores presents an opportunity to enhance the efficiency and sustainability of surrounding communities. In addition, recent studies demonstrate that implementing control algorithms considering demand flexibility strategies can lead to load and peak reductions in standalone refrigerated display cases. Because small business grocery stores operate on thin margins, the energy bill cost savings DR might provide could make a positive difference toward continued operations. Still, uncertainty remains about the extent of demand flexibility potential controls could provide when coupling refrigeration with whole building operation. To enhance economic viability and grid stability, it is essential to quantify the load flexibility capability of grocery stores. Advanced controls can optimize energy consumption by responding to load shedding, shifting, and DR events, as well as daily Time-of-Use (TOU) rates without compromising food safety. Using both quantitative data and interviews with community-based organizations, we developed a full-size store model and two small store models with controlled refrigerated cases, HVAC, and lighting systems based on actual grocery store properties. Through simulations, we have assessed load flexibility strategies with varied DR events. The results highlight potential for energy and peak reduction with advanced or basic controls. However, interviews and data indicate that more support is needed to make DR strategies consistently accessible to small grocery stores.

demand flexibility↗
DOE OSTI2022

Quantitative interpretation of time-lapse seismic data at Farnsworth field unit: Rock physics modeling, and calibration of simulated time-lapse velocity responses

Here, this study investigates the contribution of fluid saturation variation to the time-lapse velocity response by performing fluid substitution modeling. The methodology is exemplified by the time-lapse seismic monitoring of carbon dioxide at Farnsworth field unit (FWU). In order to evaluate the fluid distribution in a matured oil reservoir, the Southwest Regional Partnership (SWP) acquired multiple vertical seismic profile (VSP) surveys at different times during the CO 2 –water alternatinggas (WAG) injection period. In this work, we present a thorough methodology for computing the elastic response of the saturated rock for different fluid saturations using a site-specific petro-elastic model (PEM). The output from the PEM was combined with results from a fluid compositional model to compute the seismic velocities at times corresponding to each VSP survey. To produce a calibrated simulated response, the measured time-lapse seismic velocities were integrated into the numerical simulation model. The mismatches between the predicted and measured time-lapse velocities were minimized through an iterative calibration process using a trained artificial neural network proxy (ANN) coupled with a particle swarm optimizer (PSO). Our study indicates that the hybrid optimization workflow can effectively perform the history matching. With an accurate prediction of the hydrodynamic properties, the migration of CO 2 within the subsurface was modeled by predicting the spatial velocity distribution for a radius of 305 m around the injection well. The technology demonstrated and the expertise gained from this study can guide similar CO 2 -WAG projects.

58 GEOSCIENCES↗
DOE OSTI2018

Mass, momentum, and energy transfer in supersonic aerosol deposition processes

Aerosol deposition (AD) can lead to the formation of dense coatings via deposition of particles from a gas flow; in AD the aerosol is passed through a converging-diverging nozzle, facilitating inertial particle impaction on a desired substrate at supersonic particle velocities. Unique from thermal spray methods, AD can be applied near room temperature and unique from cold spray, in AD the aerosol is typically at atmospheric pressure upstream of the nozzle. Though AD has been successfully demonstrated previously, a number of aspects related to particle motion in AD systems remain poorly understood. In this work, we simulated compressible flow field profiles and particle trajectories for typical AD working conditions for a slit type converging-diverging nozzle with a planar substrate. In examining the fluid flow profile, we show that the velocity and pressure profiles, as well as the shock structure are sensitive to the upstream and downstream operating pressures of the nozzle. These ultimately affect particle impaction speed. Importantly, in AD, the particle drag regime is dynamic; both particle Knudsen numbers and Mach numbers can vary by orders of magnitude. To aid particle trajectory simulations, we trained a neural network to predict the drag force on the particles based on existing experimental data, theoretical limits, and new direct simulation Monte Carlo (DMSC) results. The neural network based drag law, which depends upon both Mach and Knudsen numbers, shows better agreement with the DSMC simulation data than pre-existing correlations. With it, particle trajectory simulation results reveal that for a given particle density, there exists an optimal particle diameter to maximize particle impaction speed. We also find that in AD particles undergo size dependent inertial focusing, i.e. there is a particular particle diameter where the particle deposition linewidth is minimized. Particles smaller than this diameter are underfocused, and particles larger than this are overfocused, and hence have larger deposition linewidths in both cases. Using trajectory simulations, we additionally develop a framework that can be used to evaluate the position-dependent mass, momentum and kinetic energy fluxes to the deposition substrate for any aerosol size distribution function upstream the nozzle. It is shown for typical aerosol concentrations achievable in the laboratory, the kinetic energy flux can approach a magnitude normally observed in convective heat transfer with phase change, hence translational kinetic energy to thermal energy transfer in AD is likely the key contributor to the formation of dense coatings.

42 ENGINEERING↗
DOE OSTI2020

The Development of a Generalized Riser Flow Regime Map Based Upon Higher Moment and Chaotic Statistics Using Electrical Capacitance Volume Tomography (ECVT)

Dynamic analyses have been applied to the temporal signals from an Electro Capacitance Volume Tomography instrument located near mid-height on the riser of an industrial-scale cold-flow circulating fluidized bed to characterize gas-solids flow behavior in the riser. Twelve capacitance electrodes surround the cylindrical riser over a height of 1.3 m. The instrument used a neural network deconvolution algorithm to determine the spatially resolved solids fraction recorded at 52 Hz. Experiments were carried out over a range of gas and solids flows in the transport regime using a Geldart Group B bed material, high density polyethylene with mean particle size of 880 μm. The radial solids distribution was found to vary from one-time step to the next between profiles typical of laminar and turbulent flow. The duration of time spent in each of these flow profiles depended upon the operating regime – dilute, core-annular, or fast fluidized bed. The chaotic structure of the temporal data was characterized using the three conventional approaches: the first 4 moments from the distribution of signal in time, system memory parameters from the autocorrelation function and the Hurst exponent, and analysis of the correlationentropy and correlation dimension of the attractor. These signal analysis techniques were used to clearly distinguish differences between different transport operating regimes. Specifically, it was experimentally observed that a riser transitions from core annular flow profile to dilute and dense regimes via increasing the frequency of short term transients to either dilute or dense flow profiles, respectively. A regime map was generated based upon these dynamics using solids flux and gas velocity axes. Fast fluidized, core annular, and dilute each exhibited different degree of dynamic characteristics typical of fluid dominated or particle compromising behavior. It should be noted that the magnitude for the different statistics was in the same range regardless of the regime, it was the radial profile for the statistic that changed and subsequently identified that there was a change in the regime. Finally, a reduced regime map was developed consisting of plotting the gas velocity normalized by the upper transport velocity versus the solids flux normalized by the saturation carrying capacity. The use of this reduced plot allowed the data from widely different conditions to be plotted and compared on the same<p>graph. Note that in many instances, some of the statistics identified the operating point as being in one regime while others indicated that it was in another indicating a transition region between dilute or core annular regimes and between the core annular and fast fluidization regimes. This now provides a tool that can be used to optimize process performance, identify changes in operating states, or replicate process dynamics during process scaling or changing operating parameters. </p>

Breault, Ronald↗
DOE OSTI2021

Impact Analysis of Data Integrity Attacks on FACTS-based Wide-Area Voltage Control System

Energy management system (EMS) consists of several wide-area control applications that serve as a backbone for security, stability, and reliability of the power system. Wide-area voltage control system (WAVCS), one of the critical wide-area applications, operates in coordination with local Flexible AC Transmission System (FACTS) devices to provide voltage security and optimal management of active and reactive power resources. Since the WAVCS relies on wide-area communication and data sharing devices, possible cybersecurity vulnerabilities have to be addressed to ensure the closed-loop operation of WAVCS. In this paper, we present a methodology for performing an impact analysis of cyber-attacks in WAVCS cybersecurity. In particular, different types of data integrity attacks, such as malicious tripping, fault replay, and signal altering attacks, are considered, and detailed impact analysis is conducted in a testbed environment using the Kundur's four machine two-area system. For performing an impact analysis, the transient voltage stability of the sensitive bus voltage is studied, followed by the quantitative assessment and severity ranking using the voltage profile index. Our experimental evaluation reveals that the data integrity attacks on control signals exhibit a higher attack severity than on the measurement signals. Further, the severity of these attacks varies with nature (static or dynamic), location, and types of attacks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Engineering well-expressed, V2-immunofocusing HIV-1 envelope glycoprotein membrane trimers for use in heterologous prime-boost vaccine regimens

HIV-1 vaccine immunofocusing strategies may be able to induce broadly-reactive neutralizing antibodies (NAbs). Here, we engineered a panel of diverse, membrane-resident native HIV-1 trimers vulnerable to two broad targets—the V2 apex and fusion peptide (FP). Selection criteria included i) high expression and ii) infectious function, so that trimer neutralization sensitivity can be profiled in pseudovirus (PV) assays. Initially, we boosted the expression of 17 candidate trimers by truncating gp41 and introducing a gp120-gp41 SOS disulfide to prevent gp120 shedding. "Repairs" were made to fill glycan holes and eliminate other strain-specific aberrations. A new neutralization assay allowed PV infection when our standard assay was insufficient. Trimers with exposed V3 loops, a target of non-NAbs, were discarded. To try to increase V2-sensitivity, we removed clashing glycans and modified the C-strand. Notably, a D167N mutation improved V2-sensitivity in several cases. Glycopeptide analysis of JR-FL trimers revealed near complete sequon occupation and that filling the N197 glycan hole was well-tolerated. In contrast, sequon optimization and inserting/removing glycans at other positions frequently had global "ripple" effects on glycan maturation and sequon occupation throughout the gp120 outer domain and gp41. V2 MAb CH01 selectively bound to trimers with small high mannose glycans near the base of the V1 loop, thereby avoiding clashes. Knocking in a rare N49 glycan was found to perturb gp41 glycans, increasing FP NAb sensitivity—and sometimes improving expression. Finally, a biophysical analysis of VLPs revealed that i) ~25% of particles bear Env spikes, ii) spontaneous particle budding is high and only increases 4-fold upon Gag transfection, and iii) Env+ particles express ~30–40 spikes. Taken together, we identified 7 diverse trimers with a range of sensitivities to two targets to allow rigorous testing of immunofocusing vaccine concepts.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Retrievals of Riming and Snow Density From Vertically Pointing Doppler Radars

Retrievals of ice and snow are made from Ka- and W-band zenith-pointing Doppler radars at Hyytiälä, Finland, during the snow experiment component of the Biogenic Aerosols: Effects on Clouds and Climate (2014) field campaign. In a novel optimal estimation retrieval, mean Doppler velocity is exploited to retrieve a density factor parameter, which modulates the mass, shape, terminal velocity, and backscatter cross sections of ice particles. In a case study including aggregate snow and graupel we find that snow rate and ensemble mean ice density can be retrieved to within 50% of in situ measurements at the surface using dual-frequency Doppler radar retrievals. While Doppler measurements are essential to the retrieval of particle density, the dual-frequency ratio provides a strong constraint on particle size. The retrieved density factor is strongly correlated with liquid water path, indicating that riming is the primary process by which the density factor is modulated. Using liquid water path as a proxy for riming, profiles classified as unrimed snow, rimed snow, and graupel exhibit distinct features characteristic of aggregation and riming processes, suggesting the potential to make estimates of process rates from these retrievals. We discuss the potential application of the technique to future satellite missions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Enhanced Feedstock Characterization and Modeling to Facilitate Optimal Preprocessing and Deconstruction of Corn Stover (Final Report)

This project addresses the challenge of processing corn stover by fractionating this biomass feedstock to both streamline processing and generate new potential co-products. Additionally, the project developed new field-deployable analytical tools that can be coupled with empirical models that were used to predict feedstock properties and processing performance. The overall scope of this project was: (1) identify conditions for optimal corn stover fractionation using a two- stage physical fractionation, (2) assess how physical fractionation impacts properties, partitioning of biomass, and response to processing, (3) further adapt, develop, and validate several advanced characterization tools for assessing biomass properties that can be linked to processing behavior, and (4) develop and validate predictive models based on measurements that can be performed “in the field” or “at the biorefinery gate” to predict feedstock processing behavior (preprocessing and deconstruction). The first objective employed pre-separation processing (size reduction) which was next subjected to enhanced separations to yield fractions enriched or depleted in select compositional components or properties. For the second objective, fractions were screened for their response to post-separation processing (pretreatment and enzymatic hydrolysis). Detailed characterization profiles were developed and dynamic image analysis to assess distribution of particle size and morphology. For the final objective, we utilized these tools to develop empirical models to assess the relative abundance of tissue type in order to assess fractionation efficacy and to predict fraction performance during pretreatment and enzymatic hydrolysis.

09 BIOMASS FUELS↗
DOE OSTI2022

Computational Tools and Workflows for Quantitative Risk Assessment and Decision Support for Geologic Carbon Storage Sites: Progress and Insights from the U.S. DOE’s National Risk Assessment Partnership

The 2005 Intergovernmental Panel on Climate Change (IPCC) Special Report on CCS raised the profile of CO2 capture and storage (CCS) as an important technology for reducing greenhouse gas (GHG) emissions. CCS is now recognized as a key component of most climate change mitigation scenarios. Since publication of that report the international research, development, and deployment (RD&D) community has advanced key technical aspects, clarified regulatory requirements, explored value chain and infrastructure solutions, and developed incentive paradigms to enable and promote large-scale deployment of CCS. These efforts have included research to better characterize geologic storage resources, to improve injection performance and storage efficiency, to assess and manage subsurface environmental risks, and to advance monitoring technologies to assure system conformance. These efforts have helped to build confidence in the viability of geologic carbon storage (GCS), but stakeholder concerns about long-term risks and liability associated with GCS remain a hurdle to broad acceptance and large-scale deployment of CCS. Since 2010, the U.S. DOE’s National Risk Assessment Partnership (NRAP) – a research collaboration between five contributing national laboratories – has worked to establish and demonstrate methods and tools to quantify and manage the subsurface environmental risks associated with GCS, amidst uncertainty. This work supports the Office of Fossil Energy and Carbon Management Carbon Transport and Storage Program’s goal of advancing safe and secure commercial-scale GCS deployment. To address the technical challenge of simulating the physical response of the GCS site to large-scale CO2 injection, NRAP has adopted an approach that relies on coupling computationally efficient reduced-order and/or data-driven proxy models of important system components (i.e., storage reservoir, sealing caprock, leakage pathways, intermediate formations, overlying groundwater aquifers, and the atmosphere) in integrated assessment framework. That integrated model of the physical system is complemented with fit-for purpose functionality to support site characterization and risk-related decisions. The recently released NRAP Phase II toolset includes the Open-Source Integrated Assessment Model (NRAP-Open-IAM) for evaluation of trends in leakage risk and potential impact, tools to support monitoring design optimization (Designs for Risk Evaluation and Management – DREAM v3.0 and Passive Seismic Monitoring Tool - PSMT), and tools for state of stress evaluation (State-of-Stress Analysis Tool - SOSAT) and forecasting induced seismicity risk. The NRAP team has also released a pair of reports describing conceptual workflows to incorporate physics-based, quantitative risk assessment into many of the design, planning, operation, and closure decisions for GCS projects. An online catalogue highlights published studies where these tools and methods are demonstrated. In this presentation, the utility of these products to assess risks and address key stakeholder questions will be highlighted through examples, and related insights about the safety and security of geologic carbon storage in qualified storage sites will be discussed. The prospect of rapid, large-scale deployment of GCS technology to aggressively reduce anthropogenic CO2 emissions requires careful consideration of interference between multiple commercial-scale storage projects within a basin. Going forward, NRAP is expanding and adapting site-scale risk quantification tools and methods to enable assessment of risks and inform management decisions for basin-scale deployment. Increasingly, this work will leverage next-generation approaches for surrogate modelling, fast prediction, and advanced visualization enabled by machine learning and artificial intelligence to promote virtual learning, scenario evaluation, and augment risk-based decision making.

quantitative risk assessment, geologic carbon stor↗
DOE OSTI2020

Muon radiography applied to volcanoes imaging: the MURAVES experiment at Mt. Vesuvius

Muon radiography is a technique based on the measurement of absorption profiles of muons as they pass through matter. This measurement allows to obtain an image of the inner structure of large volume objects and is suitable to be applied in several fields, such as volcanology, archaeology and civil engeneering. One of the main applications concerns the study of volcanic structures; indeed it is possible to use this technique to measure the mass distribution inside the edifice of a volcano providing useful information to better understand the possible eruption mechanisms. The MURAVES (MUon RAdiography of VESuvius) project aims to the study of the summital cone of Mt. Vesuvius near Naples in Italy, one of the most dangerous active volcanoes in the world. The MURAVES apparatus is a modular, robust muon hodoscope system with a low power consumption, optimized to be used in inhospitable environments like the surroundings of volcanoes. The complete detection system is an array of identical tracking modules, each with an area of 1 m2, based on the use of plasic scintillators. The technologies, the status and the data analysis strategy of the experiment will be presented in this paper.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Constitutive and inducible oleoresin defenses share genetic architectures and mechanisms in Pinus taeda

The oleoresin defense system of loblolly pine (Pinus taeda) protects trees from insects and pathogens and is an important source of renewable biofuels and chemicals, but the genetic basis of oleoresin production is poorly understood. We characterized the genetic architecture of oleoresin flow, resin canal number, stem wood terpene content, and monoterpene composition in two clonal populations of P. taeda. We used quantitative genetic analyses, genome-wide association studies (GWASs), multiplex network learning, and gene expression profiling to elucidate shared gene networks underlying defense traits and to identify high-quality candidates for breeding and engineering loblolly pine. Genetic analyses revealed polygenic inheritance and trait-to-trait correlations provide strong evidence for shared genes regulating constitutive and induced oleoresin flow. We identified 236 single nucleotide polymorphisms associated with oleoresin flow, resin canal number, and terpene composition and highlight candidate genes likely involved in terpene biosynthesis, cambial meristem reprogramming, and pathogen perception and immune signaling. Fourteen GWAS candidates were methyl jasmonate-responsive in tissues where resin canals initiate and terpene production occurs. Integrating quantitative genetics, GWAS, gene expression, and multiplex network analyses enabled the prioritization of high-quality candidate genes. This work advances the development of more resilient loblolly pine optimized for ecological performance, renewable chemical, and biofuel production.

genome-wide association study↗
DOE OSTI2021

Development of Electro-chemical Battery Model for Plug-and-Play Eco-system Library

Energy storage components are fundamental to the concept of an Integrated Energy System (IES). They serve to store surplus energy during low-demand periods for later release when other IES components (i.e., Secondary Energy Source, Balance of Plant, etc.) would otherwise have to operate flexibly. This provision for storage avoids high-amplitude power ramps in these components thereby limiting thermal and mechanical stresses to their internals and providing for extended service life. This report describes a dynamic model that has been developed for an electrochemical battery. The lithium-ion (Li-ion) cell was selected as representative technology. The battery model was developed in the Dymola simulation environment and meets the requirements of the ecosystem plug-and-play library. The model accurately describes the electric dynamic response of a Li-ion battery for an imposed charging/discharging power profile. The corresponding physical limitations related to over-power scenarios, and the impact of the residual state of charge are accounted for in the model. A literature review of the major degradation processes affecting Li-ion batteries was performed. Given the purposes of the CTD-IES project, the progressive fade of the installed capacity, the reduction of the round-trip efficiency, and the limits on the number of charging/discharging cycles are aspects that need to be taken into account in techno-economic analyses. The modeling of these degradation phenomena becomes crucial when predictions over long time horizons (capacity expansion) are made. For each one of these phenomena, a brief description is given, and some figures to be implemented in the HERON optimization algorithm are presented.

25 ENERGY STORAGE↗
DOE OSTI2025

EMPDF : inferring the Milky Way mass with data-driven distribution function in phase space

We introduce the emPDF (empirical distribution function), a novel dynamical modelling method that infers the gravitational potential from kinematic tracers with optimal statistical efficiency under the minimal assumption of steady state. emPDF determines the best-fitting potential by maximizing the similarity between instantaneous kinematics and the time-averaged phase-space distribution function (DF), which is empirically constructed from observation upon the theoretical foundation of oPDF (Han et al. 2016). This approach eliminates the need for presumed functional forms of DFs or orbit libraries required by conventional DF- or orbit-based methods. emPDF stands out for its flexibility, efficiency, and capability in handling observational effects, making it preferable to the popular Jeans equation or other minimal assumption methods, especially for the Milky Way (MW) outer halo where tracers often have limited sample size and poor data quality. We apply emPDF to infer the MW mass profile using Gaia DR3 data of satellite galaxies and globular clusters, obtaining enclosed masses of M (,r) = 26±8, 46±8, 90±13⁠, and 149±40 x 10 10 M ⊙ at r = 30, 50, 100⁠, and 200 kpc, respectively. These are consistent with the updated constraints from simulation-informed DF fitting (Li et al. 2020). While the simulation-informed DF offers superior precision owing to the additional information extracted from simulations, emPDF is independent of such supplementary knowledge and applicable to general tracer populations. emPDF is currently implemented for tracers with complete 6D kinematics within spherical potentials, but it can potentially be extended to address more general problems.

Astrophysics of Galaxies (astro-ph.GA)↗
DOE OSTI2022

Modeling the cooldown of cryocooler conduction-cooled devices

Cryocooler conduction cooled devices can experience significant cooldown time due to lower available cooling capacity compares to convection cooled devices. Therefore, the cooldown time is an important design parameter for conduction cooled devices. This article introduces a framework developed in Python for calculating the cooldown profiles and cooldown time of cryocooler conduction-cooled devices such as superconducting magnets and accelerator cavities. The cooldown time estimation problem is essentially a system of ordinary first-order differential equations comprising the material properties (temperature dependent thermal conductivity and specific heat capacity) of the components intertwined with the prevailing heat transfer channels (conduction, radiation, and heat flow across pressed contacts) and the cryocooler capacity. The formulation of this ODE system is first presented. This ODE system is then solved using the in-built Python library odeint. A case study is presented comprising a small cryocooler conduction-cooled copper stabilized niobium-titanium magnet. The case study is supplemented with the Python script enabling the reader to simply tweak the device design parameters and optimize the design from the point of view of slow/fast cooldown.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Fingerprinting shock-induced deformations via diffraction

Abstract During the various stages of shock loading, many transient modes of deformation can activate and deactivate to affect the final state of a material. In order to fundamentally understand and optimize a shock response, researchers seek the ability to probe these modes in real-time and measure the microstructural evolutions with nanoscale resolution. Neither post-mortem analysis on recovered samples nor continuum-based methods during shock testing meet both requirements. High-speed diffraction offers a solution, but the interpretation of diffractograms suffers numerous debates and uncertainties. By atomistically simulating the shock, X-ray diffraction, and electron diffraction of three representative BCC and FCC metallic systems, we systematically isolated the characteristic fingerprints of salient deformation modes, such as dislocation slip (stacking faults), deformation twinning, and phase transformation as observed in experimental diffractograms. This study demonstrates how to use simulated diffractograms to connect the contributions from concurrent deformation modes to the evolutions of both 1D line profiles and 2D patterns for diffractograms from single crystals. Harnessing these fingerprints alongside information on local pressures and plasticity contributions facilitate the interpretation of shock experiments with cutting-edge resolution in both space and time.

36 MATERIALS SCIENCE↗
DOE OSTI2023

In Vitro Thrombogenicity Testing of Biomaterials in a Dynamic Flow Loop: Effects of Length and Quantity of Test Samples

Abstract The results of in vitro dynamic thrombogenicity testing of biomaterials and medical devices can be significantly impacted by test conditions. To develop and standardize a robust dynamic in vitro thrombogenicity tool, the key test parameters need to be appropriately evaluated and optimized. We used a flow loop test system previously developed in our laboratory to investigate the effects of sample length and the number of samples per test loop on the thrombogenicity results. Porcine blood heparinized to a donor-specific target concentration was recirculated at room temperature through polyvinyl chloride (PVC) tubing loops containing test materials for 1 h at 200 mL/min. Four test materials (polytetrafluoroethylene (PTFE), latex, PVC, and silicone) with various thrombotic potentials in two sample lengths (12 and 18 cm) were examined. For the 12-cm long materials, two different test configurations (one and two samples per loop) were compared. Thrombogenicity was assessed through percent thrombus surface coverage, thrombus weight, and platelet count reduction in the blood. The test system was able to effectively differentiate the thrombogenicity profile of the materials (latex > silicone > PVC ≥ PTFE) at all test configurations. Increasing test sample length by 50% did not significantly impact the test results as both 12 and 18 cm sample lengths were shown to equally differentiate thrombotic potentials between the materials. The addition of a second test sample to each loop did not increase the test sensitivity and may produce confounding results, and thus a single test sample per loop is recommended.

Engineering↗