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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 523 records · Page 29

All sources NASA NTRS DOE OSTI

DOE OSTI2021

Key Learnings from Hydraulic Fracturing Test Site - 2 (HFTS-2), Delaware Basin

Hydraulic fractures (HF) play a dominant role in oil and gas production from unconventional reservoirs, fracture characteristics, geometry, and extent are generally not well known and are typically inferred from various monitoring methods or subsurface models. The Hydraulic Fracturing Test Site-2 (HFTS-2) is a field-based research experiment performed in the Wolfcamp formation of the Permian (Delaware) Basin. HFTS-2, a unique joint industry program (JIP) that brings together government, academia, and industry, focused on field data acquisition and interpretation. The project has built a comprehensive HF research dataset that includes microseismic (MS), 1,500 ft of core, diagnostic formation injection tests (DFIT), fluid characterization, advanced logs, geochemistry, downhole gauges, varying completions, and permanent fiber optic (FO) cable in vertical and horizontal wells. These data were integrated and used to characterize HF geometry/dimensions and resulting depletion profiles, gain insights for completion design, and achieve a better understanding of parent well depletion effects on child well performance. The analysis and integration of the comprehensive HFTS-2 diagnostics dataset provide insights for optimal well placement and completions and improves understanding about the effects of parent well depletion. Furthermore, this dataset can be used to blind test and develop subsurface workflows for unconventional resources. Key learnings from HFTS-2 and the new technologies tested can easily be transferred to other unconventional plays.

58 GEOSCIENCES↗

DOE OSTI2022

A multi-modal scanning system to digitize CBRNE emergency response scenes

A handheld system developed to digitize a contextual understanding of the scene at a chemical, biological, radiological, nuclear and/or explosives (CBRNE) events is described. The system uses LiDAR and cameras to create a colorized 3D model of the environment, which helps domain experts that are supporting responders in the field. To generate the digitized model, a responder scans any suspicious objects and the surroundings by carrying the system through the scene. The scanning system provides a real-time user interface to inform the user about scanning progress and to indicate any areas that may have been missed either by the LiDAR sensors or the cameras. Currently, the collected data are post-processed on a different device, building a colorized triangular mesh of the encountered scene, with the intention of moving this pipeline to the scanner at a later point. The mesh is sufficiently compressed to be sent over a reduced bandwidth connection to a remote analyst. Furthermore, the system tracks fiducial markers attached to diagnostic equipment that is placed around the suspicious object. The resulting tracking information can be transmitted to remote analysts to further facilitate their supporting efforts. The paper will discuss the system's design, software components, the user interface used for scanning a scene, the necessary procedures for calibration of the sensors, and the processing steps of the resulting data. The discussion will close by evaluating the system's performance on 11 scenes.

Prins, Nicholas↗

DOE OSTI2025

A new method for diagnosing effective radiative forcing from aerosol–cloud interactions in climate models

Aerosol–cloud interactions (ACIs) are a leading source of uncertainty in estimates of the historical effective radiative forcing (ERF). One reason for this uncertainty is the difficulty in estimating the ERF from aerosol–cloud interactions (ERFaci) in climate models, which typically requires multiple calls to the radiation code. Most commonly used methods also cannot disentangle the contributions from different processes to ERFaci. Here, we develop a new, computationally efficient method for estimating the shortwave (SW) ERFaci from liquid clouds using histograms of monthly averaged cloud fraction partitioned by cloud droplet effective radius (r e ) and liquid water path (LWP). Multiplying the histograms with SW cloud radiative kernels gives the total SW ERFaci from liquid clouds, which can be decomposed into contributions from the Twomey effect, LWP adjustments, and cloud fraction (CF) adjustments. We test the method with data from five CMIP6-era models, using the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite instrument simulator to generate the histograms. Our method gives similar total SW ERFaci estimates to other established methods in regions of prevalent liquid cloud and indicates that the Twomey effect, LWP adjustments, and CF adjustments have contributed -0.34 ± 0.23, -0.22 ± 0.13, and -0.09 ± 0.11 W m -2 , respectively, to the effective radiative forcing of the climate since 1850 in the ensemble mean (95 % confidence). These results demonstrate that widespread adoption of a MODIS r e –LWP joint histogram diagnostic would allow the SW ERFaci and its components to be quickly and accurately diagnosed from climate model outputs, a crucial step for reducing uncertainty in the historical ERF.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Emissions and Flame Structure Assessment of Aeroengine Micromixing Injectors for Lean Direct Injection of Hydrogen and Hydrogen/Natural Gas Blends

Abstract The present study focuses on whether adapting low emissions liquid fuel injection concepts can be applied to gaseous mixtures. The goal is to develop an injector with specific geometric characteristics that will achieve the lowest emissions. This is conducted by evaluating emissions and flame diagnostics on a set of test hardware that has been developed for combustion of pure hydrogen and hydrogen/methane mixtures. The current test hardware adapts lean direct injection concepts from aeroengine injectors to a ground-based engine based on target flows associated with a Solar Turbines Industrial Engine gas turbine. A statistical test plan was developed to assess these geometric characteristics using a three level Box Behnken design. The test plan investigates the effect of injector flow splits, air swirl, fuel swirl, pressure drop, preheat temperature, fuel composition, and the adiabatic flame temperature on the flame structure and emissions performance. A total of 16 injectors were considered for a total of 688 test points for emission and imaging data. Emissions data were reported on a mass basis in ng/J and chemical reactor network analysis were conducted to further interpret emissions behavior. Images were also captured to analyze the flame structure features of interest including reaction volume, flame length, flame spread, and flame width. With these results, a predictive model for emissions was made to conclude the most optimal injector configuration is to have the highest level of air split (more volume of air through the injector plate versus the injector) and air swirl angle for both methane and hydrogen gas mixtures. The predictive emissions level for all of these cases were below 10 ng/J.

08 HYDROGEN↗

DOE OSTI2024

IDAES-PSE 2.5.0 Release

AS↗

DOE OSTI2020

Hybrid Analytics Solution for Power Plant Operations

Expert Microsystems, Inc., MapEx Software Inc. and XMPLR Energy LLC have teamed to submit a proposal to the US Department of Energy’s Office of Fossil Energy to improve the efficiency, reliability and flexibility of existing coal-based power plants. The project, titled Hybrid Analytics Solution to Improve Coal Power Plant Operations (the “Hybrid Analytics” project), will develop, demonstrate and commercialize a novel approach that integrates two proven real-time monitoring techniques. The Hybrid Analytics approach integrates into a single, integrated solution: a) an established, advanced data-driven analytics solution that includes artificial intelligence, advanced pattern recognition and machine-learning techniques and b) a well-proven, first principle thermal heat balance model solution. The future role of coal plants will depend on the ability to cycle and follow loads to meet marginal power demands, accommodate renewables and support the grid. Essential to success in this new role is a plant’s ability to maintain high reliability, efficiency and flexibility. However, these changing operational demands put significant stresses on power plant components that directly impact the ability to deliver these requirements. In the past, plants have independently monitored performance using physics-based solutions (heat rate, boiler losses, etc.) and reliability using data-driven analytics (advanced pattern recognition). The Hybrid Analytics solution integrates both approaches to enhance fault detection, provide automated diagnostics and estimates of remaining time to act, and provide critical, enhanced and accurate real-time information to coal plant operators. As a result, coal plants can improve efficiency, reliability, and flexibility and can cost-effectively maintain their key role in the power delivery system.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2023

Hypervelocity impact in stellar media: heat shielding, shock fronts and ablation clouds

The Frontier Plasma Science experiments proposed by our team will model the processes occurring during spacecraft atmospheric entries and meteorite planetary collisions by inserting material targets into the Scrape off Layer (SOL) and edge plasma of a tokamak. This project will investigate important plasma-material processes during high-enthalpy atmospheric entries, including heat flux generation and material ablation. Of particular interest is to explore heat and particle flux detachment in front of the sample using concepts and techniques developed in the latest studies of divertor detachment. Exploration missions to the Solar System’s gaseous giants and hyperbolic re-entries into the Earth’s atmosphere require spacecraft that can withstand high velocity (>10 km/s), high heat fluxes (>10 MW/m2), and corresponding enthalpies. Ablative materials have been used as thermal shields to protect the spacecraft from severe heating during entry. However, developing high enthalpy ablating materials is challenging due to the lack of adequate ground testing facilities. Our team stated that the performance of candidate shielding materials could be assessed in a laboratory environment with multiple in-situ diagnostics, which was enabled by the progress in the tokamak research. Modern machines feature relatively long discharges (~10 s) with well-controlled stable plasma conditions at the edge where the heat flux and the flow speed are similar to those experienced during atmospheric entries. The experiments were carried out at the DIII-D National Fusion Facility in San Diego, CA, operated by General Atomics (GA) for the DoE.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

(Paper) TRIPWIRE: Multi-modal Distributed Sensing For Repository Verification

Underground geological repositories for storing used nuclear fuel are being planned and developed around the world. Research is being performed to understand technical aspects of sealing entombed materials and underground repositories to ensure the radiological and nuclear materials remain contained. To support safeguards verification for these facilities research at Idaho National Laboratory (INL) is underway to develop and demonstrate a multi-modal sensor system, TRIPWIRE, for containment verification in inaccessible radiological and nuclear waste repositories. The TRIPWIRE system will continuously monitor ionizing radiation and electromagnetic fields in the vicinity of emplaced nuclear materials buried in a repository, reporting on disturbances with a real-time alarm control station. The system will use long-length scintillating fiber bundles (SFBs) to perform area radiation monitoring; these will be coupled to kilometer-scale multimodal optical communication fibers – all light sensors and electronic components used with this system will be located above ground. Electromagnetic fields, and changes in local dielectric conditions caused by intrusion and soil movement, will be monitored using commercial grade, ported "leaky" coaxial cables (PCCs), with control electronics also located above ground. Tamper-indicating self-diagnostic assessments will be done using optical and electronic time domain reflectometry in the SFBs and PCCs, respectively. The result will be a long, kilometer-scale multi-modal SFB-PCC system. Simulation and modeling are being used to inform the work and a demonstration of the system's utility is planned at a nuclear storage facility in the future.

98 - NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL↗

DOE OSTI2021

First observation of increased DT yield over prediction due to addition of hydrogen

Here, in a number of reported instances, implosions utilizing fuel mixtures have resulted in anomalously low fusion yields below those predicted by radiation-hydrodynamics simulations. Inter-species ion diffusion has been suggested as a possible cause of the observed yield degradation in fuel mixture implosions. An experimental platform utilizing hydro-equivalent deuterium–tritium (DT), deuterium–tritium–hydrogen (DTH), and deuterium-tritium-helium3 (DT 3 He) capsule implosions was developed to determine whether the inter-species ion diffusion theory may describe the resulting fuel mixture implosion behavior. The implosion experiments were performed at the Omega laser facility. X-ray images and shell areal density diagnostics results show that the hydro-equivalent three capsules (DT, DTH, and DT 3 He) have similar compression behavior. However, nuclear yield deviation was observed from the scaling determined using a fusion yield formula. In the DT 3 He mixture, a reduced yield of a factor of 0.65 ± 0.13 was observed, which is similar to a yield reduction observed in D 3 He mixture by Rygg et al. (i.e., Rygg effect). In contrast, in the DTH mixture, a factor of 1.17 ±0.15 yield increase was observed, which we named the inverse Rygg effect. The yield increase observed in the DTH mixture is consistent with the inter-species ion diffusion theory where lighter H diffuses away from the core and concentrated DT in the core produces higher yield. An inter-species ion diffusion model, the Zimmerman–Paquette–Kagan–Zhdanov model, implemented in a Lagrangian radiation-hydrodynamics fluid code, was also used to analyze the present data, without the need to assume hydrodynamic equivalence of the capsules, but it does not completely explain the DTH or DT 3 He capsules although its effects are in the correct direction. Simulation-based Bayesian inference was used in the latter analysis to quantify the uncertainty in the numerical simulations. The simulation-based analysis resulted in an inferred Rygg-effect yield decrease factor of 0.91 ± 0.02 for the DT 3 He mixture, and an inferred inverse-Rygg yield increase factor of 1.21 ± 0.04 for the DTH mixture, based on simulations ignoring ion diffusion.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Reflected shock-initiated ignition probed via simultaneous lateral and endwall high-speed imaging with a transparent, cylindrical test-section

A TRAnsparent cylindrical (TRAC) shock tube test section has been developed to explore the ignition structure behind reflected shockwaves via simultaneous lateral and endwall high-speed imaging using three fuel/oxidizer mixtures: 0.1% n-C 7 H 16 /1.10% O 2 /4.14% N 2 /94.66% Ar, 0.1% iC 8 H 18 /1.25% O 2 /4.69% N 2 /93.96% Ar, and 5% CH 4 /10% O 2 /85% CO 2 . During mild ignition, the first exothermic centers were located outside of the observable test section. It is shown that with increasing temperature the far-wall ignition events move closer to the endwall, until a strong ignition is achieved. The temperature gradients that promote mild ignition were quantified and were found to have a slight dependence on fuel with the RMS temperature gradients being 0.80% for n-heptane and 1.07% for isooctane. The impact of temperature gradients on metrics used to improve kinetic models, such as species time histories, is noteworthy. From this temperature gradient, an experimental correlation is provided to estimate the transition temperature from mild to strong ignition for a mixture. The effect of diagnostic location in non-homogeneous reactions is quantified in reference to ignition delay. In conclusion, the unique and insightful perspective on the ignition process under heavy shock bifurcation is also discussed.

02 PETROLEUM↗

DOE OSTI2024

The CXSFIT spectral fitting code: Past, present and future

Magnetically confined plasma experiments generate a wealth of spectroscopic data. The first step toward extracting physical parameters is to fit a spectral model to the often complex spectra. The CXSFIT (Charge eXchange Spectroscopy FITting) spectral fitting code was originally developed for fitting charge exchange spectra on JET from the late 1980s onward and has been further developed over decades to keep up with the needs of the users. The primary use is to efficiently fit a large number of spectra with many constrained Gaussian spectral lines of which the physical parameters can be coupled in a user-friendly manner. More recent additions to the code include time-dependent couplings between parameters, flexible background subtraction, and a non-linear coupling scheme between fit parameters. The latter was a pre-requisite for implementing Zeeman and motional Stark effect multiplets in the library of spectral features. The ability to save and replay “fit recipes,” even when multiple iterations are required, has ensured the traceability of the results and is one of the keys to the longevity and success of the code. The code is also in use on other tokamaks (AUG, ST-40) and to fit data from other spectroscopic diagnostics on JET. In this paper, we document the current capabilities and philosophy behind the structure of the code, including some of the algorithms used to calculate spectral features numerically efficiently. We also provide an outline of how CXSFIT could be transferred into a framework that would be able to meet the spectral fitting requirements of future devices, such as ITER.

Delabie, Ephrem G.↗

DOE OSTI2022

Diagnostics for multiple frequency heating and investigation of underlying processes

The development of new facilities routinely challenges ion source designers to build and operate sources that can achieve ever higher beam intensities and energies. As shown in this work, electron cyclotron resonance ion sources have proven to be extremely capable in meeting these challenges through the production of intense beams of medium and high-charge state ions. As performance boundaries are pushed, source stability becomes an issue as does the technology required to meet the challenge. Multiple frequency heating, the simultaneous use of two or more plasma heating frequencies, is a powerful tool in meeting the simultaneous need of intensity and stability. Relatively straightforward to utilize, the technique has been employed at numerous facilities to increase beam current and achievable charge state while also stabilizing the plasma. Its application has expanded the operational boundaries of existing and next generation sources, demonstrating that these devices have not yet achieved their full operational potential. To better understand the underlying physics, the diagnostics used to probe the source operational boundaries and the plasma properties have become increasingly sophisticated. In concert with detailed modeling, they are beginning to provide insight into the heating mechanism and, with that, the prospect of future advances.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

A Vertically Resolved MSE Framework Highlights the Role of the Boundary Layer in Convective Self-Aggregation

Abstract Convective self-aggregation refers to a phenomenon in which random convection can self-organize into large-scale clusters over an ocean surface with uniform temperature in cloud-resolving models. Previous literature studies convective aggregation primarily by analyzing vertically integrated (VI) moist static energy (MSE) variance. That is the global MSE variance, including both the local MSE variance at a given altitude and the covariance of MSE anomalies between different altitudes. Here we present a vertically resolved (VR) MSE framework that focuses on the local MSE variance to study convective self-aggregation. Using a cloud-resolving simulation, we show that the development of self-aggregation is associated with an increase of local MSE variance, and that the diabatic and adiabatic generation of the MSE variance is mainly dominated by the boundary layer (BL; the lowest 2 km). The results agree with recent numerical simulation results and the available potential energy analyses showing that the BL plays a key role in the development of self-aggregation. Additionally, we find that the lower free troposphere (2–4 km) also generates significant MSE variance in the first 15 days. We further present a detailed comparison between the global and local MSE variance frameworks in their mathematical formulation and diagnostic results, highlighting their differences.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Microbial Community Composition in Deep‐Subsurface Reservoir Fluids Reveals Natural Interwell Connectivity

Abstract The identification of natural fractures and the wells they connect is crucial for the development of geological reservoirs because it may have an important impact on reservoir model construction and hydraulic fracture propagation. In this study we investigated the use of a novel data source, the microbial community composition in the reservoir formation fluids, for identification of interwell connectivity caused by natural fractures. We verified this concept at a newly developed mesoscale enhanced geothermal system (EGS) field testbed located 4,850 ft (1,478 m) beneath ground surface at the Sanford Underground Research Facility in Lead, SD. Fluids produced at or near the EGS testbed were sampled and subjected to high‐throughput 16S rRNA gene amplicon sequencing to analyze the microbial community profile therein. Despite the typically substantial heterogeneity across the community profiles of samples spatially distributed (10 m to 1.9 km apart) throughout the site, samples from two wells at the EGS testbed showed highly similar microbial community composition, suggesting the two wells intersected the same natural fracture. This evidence of natural connectivity between the two wells at the EGS testbed was later corroborated by core log analysis and sewer camera surveys into the boreholes. Besides the field case described in this study, microbial community composition as a reservoir diagnostic tool would be applicable in a much broader context such as unconventional hydrocarbon exploitation, groundwater reservoir characterization, and environmental remediation, adding valuable “hard” data capable of pinpointing the origins of fluids unambiguously.

Zhang, Yuran↗

DOE OSTI2024

Overview of T and D–T results in JET with ITER-like wall

In 2021 JET exploited its unique capabilities to operate with T and D–T fuel with an ITER-like Be/W wall (JET-ILW). This second major JET D–T campaign (DTE2), after DTE1 in 1997, represented the culmination of a series of JET enhancements—new fusion diagnostics, new T injection capabilities, refurbishment of the T plant, increased auxiliary heating, in-vessel calibration of 14 MeV neutron yield monitors—as well as significant advances in plasma theory and modelling in the fusion community. DTE2 was complemented by a sequence of isotope physics campaigns encompassing operation in pure tritium at high T-NBI power. Carefully conducted for safe operation with tritium, the new T and D–T experiments used 1 kg of T (vs 100 g in DTE1), yielding the most fusion reactor relevant D–T plasmas to date and expanding our understanding of isotopes and D–T mixture physics. Furthermore, since the JET T and DTE2 campaigns occurred almost 25 years after the last major D–T tokamak experiment, it was also a strategic goal of the European fusion programme to refresh operational experience of a nuclear tokamak to prepare staff for ITER operation. The key physics results of the JET T and DTE2 experiments, carried out within the EUROfusion JET1 work package, are reported in this paper. Progress in the technological exploitation of JET D–T operations, development and validation of nuclear codes, neutronic tools and techniques for ITER operations carried out by EUROfusion (started within the Horizon 2020 Framework Programme and continuing under the Horizon Europe FP) are reported in (Litaudon et al Nucl. Fusion accepted), while JET experience on T and D–T operations is presented in (King et al Nucl. Fusion submitted).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

IDAES-PSE 2.6.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications. IDAES-PSE 2.6.0 Release Highlights Upcoming Changes IDAES will be switching to the new Pyomo solver interface in the next release. Whilst this will hopefully be a smooth transition for most users, there are a few important changes to be aware of. The new solver interface uses a different version of the IPOPT writer (“ipopt_v2”) and thus any custom configuration options you might have set for IPOPT will not carry over and will need to be reset. By default, the new Pyomo linear presolver will be activated with ipopt_v2. Whilst are working to identify any bugs in the presolver, it is possible that some edge cases will remain. IDAES will begin deploying a new set of scaling tools and APIs over the next few releases that make use of the new solver writers. The old scaling tools and APIs will remain for backward compatibility but will begin to be deprecated. New Models, Tools and Features New Intersphinx extension automatically linking Jupyter notebook examples to project documentation New end-to-end diagnostics example demonstrated on a real problem New complementarity formulation for VLE with cubic equations of state, backward compatibility for old formulation New solver interface with presolve (ipopt_v2) in support of upcoming changes to the initialization and APIs methods, with default set to ipopt to maintain backwards compatibility; this will deprecate once all examples have been updated New forecaster and parameterized bidder methods within grid integration library Updated surrogates API and examples to support Keras 3, with backwards compatibility for older formats such as TensorFlow SavedModel (TFSM) Updated costing base dictionary to include the 2023 cost year index value Updated ProcessBlock to include information on the constructing block class Updated Flowsheet Visualizer to allow visualize() method to return value and functions Bug Fixes Fixed bug in the Modular Property Framework that would cause errors when trying to use phase-based material balances with phase equilibria. Fixed bug in Modular Properties Framework that caused errors when initializing models with non-vapor-liquid phase equilibria. Fixed typos flagged by June update to crate-ci/typos and removed DMF-related exceptions Minor corrections of units of measurement handling in power plant waste/transport costing expressions, control volume material holdup expressions, and BTX property package parameters Fixed throwing >7500 numpy deprecation warnings by replacing scalar value assignment with element extraction and item iteration calls Testing and Robustness Migrated slow tests (>10s) to integration, impacting test coverage but also yielding a nearly 30% decrease in local test runtime Pinned pint to avoid issues with older supported Python versions Pinned codecov versions to avoid tokenless upload behavior with latest version Bumped extensions to version 3.4.2 to allow pointing to non-standard install location Deprecations and Removals Python 3.8 is no longer supported. The supported Python versions are 3.9 through 3.12 The Data Management Framework (DMF) is no longer supported. Importing idaes.core.dmf will cause a deprecation warning to be displayed until the next release The SOFC Keras surrogates have been removed. The current version of the SOFC surrogate model in the examples repository is a PySMO Kriging model.

AS↗

DOE OSTI2025

Housing-Performance Atlas of Baltimore Row Homes: Archetype-Based Multi-Hazard Baseline of Energy, Heat, Survivability, and Durability

Baltimore’s historic row-home neighborhoods face escalating risks to energy, heat, and durability under intensifying climate stress. This study develops a Housing-Performance Atlas that quantifies multi-hazard performance for eight representative archetypes using DesignBuilder/EnergyPlus Version 7.3.1.003, under Baltimore TMY3 boundary conditions. Performance is evaluated across the following four adaptation domains: energy use intensity, passive survivability during 72 h outage events, roof overheating exposure (>150 °F exceedance hours), and material service life derived from ISO 15686 and synthesized into Lean and Full Deficit Indices for comparative resilience ranking. Results show that EUI ranged from 46.7 to 67.6 kBtu ft −2 ·yr −1 , survivability from 0 to 23 h, and roof temperatures exceeded 150 °F for 150–210 h, shortening roof service life by up to 10 years. Composite Lean and Full Deficit Indices ranged 7.8–92.4, ranking Model 5 (end-unit, flat roof, two-story with basement) as the most resilient configuration and Model 8 (end-unit, pitched roof, three-story above-grade) as the least resilient due to compounded overheating and energy losses. Heat-related domains accounted for nearly 70% of overall resilience deficits, confirming thermal safety and roof reflectivity as retrofit priorities. The Housing-Performance Atlas establishes a reproducible diagnostic framework linking simulation, service life, and resilience metrics to guide cost-effective, climate-responsive retrofits in Baltimore’s aging urban housing stock.

Housing-Performance atlas↗

DOE OSTI2026

Thermal and electromechanical response of ultra-thin carbon-strip polarimeter targets in relativistic bunched beams

Thin carbon-strip targets provide fast relative hadron beam polarimetry, but their response in intense relativistic bunched beams is not governed by local stopping-power heating alone. We develop a coupled response model that combines beam-target overlap, secondary-electron escape, retained heat, target motion, transient heat transport, RF-induced strip-end heating, beam-induced forces, resistance changes, and slack-strip deformation. RHIC target observations constrain the relevant motion, force, and nonlocal-heating scales and show that target survival depends on both beam-center heating and electromagnetic boundary conditions near the strip ends. Applying the model to Booster, AGS, RHIC, and EIC proton and 3 He cases shows that the RHIC proton lifetime scale is reproduced at the order-of-magnitude level, while the RHIC target-holder fin results require the additional RF/end-heating mechanism. For EIC proton flattop operation, carbon-strip polarimetry may remain viable only with reduced dwell time, sufficient detector acceptance, and suppression of RF-induced end heating. For cooled-emittance 3 He, the calculated sublimation-loss scale is far beyond a straightforward RHIC-like carbon-strip extrapolation. Conventional carbon strips are therefore unlikely to remain viable for the most demanding EIC light-ion cases without major changes in target motion, target technology, or diagnostic concept.

43 PARTICLE ACCELERATORS↗