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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,081 records · Page 60

Accelerating $\mathrm{LHC}$ event generation with simplified pilot runs and fast $\mathrm{PDF}$s

Poor computing efficiency of precision event generators for LHC physics has become a bottleneck for Monte-Carlo event simulation campaigns. We provide solutions to this problem by focusing on two major components of general-purpose event generators: The PDF evaluator and the matrix-element generator. For a typical production setup in the ATLAS experiment, we show that the two can consume about 80% of the total runtime. Using NLO simulations of pp→ℓ + ℓ - +jets and pp→$t\bar{t}$+jets as an example, we demonstrate that the computing footprint of LHAPDF and SHERPA can be reduced by factors of order 10, while maintaining the formal accuracy of the event sample. The improved codes are made publicly available.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

t -channel dark matter models – a whitepaper

This report, summarising work achieved in the context of the LHC Dark Matter Working Group, investigates the phenomenology of t -channel dark matter models, spanning minimal setups with a single dark matter candidate and mediator to more complex constructions closer to UV-complete models. For each considered class of models, we examine collider, cosmological and astrophysical implications. In addition, we explore scenarios with either promptly decaying or long-lived particles, as well as featuring diverse dark matter production mechanisms in the early universe. By providing a unified analysis framework, numerical tools and guidelines, this work aims to support future experimental and theoretical efforts in exploring t -channel dark matter models at colliders and in cosmology.

Arina, Chiara [Universite Catholique de Louvain, L↗

AEDGE: Atomic Experiment for Dark Matter and Gravity Exploration in Space

We propose in this White Paper a concept for a space experiment using cold atoms to search for ultra-light dark matter, and to detect gravitational waves in the frequency range between the most sensitive ranges of LISA and the terrestrial LIGO/Virgo/KAGRA/INDIGO experiments. This interdisciplinary experiment, called Atomic Experiment for Dark Matter and Gravity Exploration (AEDGE), will also complement other planned searches for dark matter, and exploit synergies with other gravitational wave detectors. We give examples of the extended range of sensitivity to ultra-light dark matter offered by AEDGE, and how its gravitational-wave measurements could explore the assembly of super-massive black holes, first-order phase transitions in the early universe and cosmic strings. AEDGE will be based upon technologies now being developed for terrestrial experiments using cold atoms, and will benefit from the space experience obtained with, e.g., LISA and cold atom experiments in microgravity. This paper is based on a submission (v1) in response to the Call for White Papers for the Voyage 2050 long-term plan in the ESA Science Programme. ESA limited the number of White Paper authors to 30. However, in this version (v2) we have welcomed as supporting authors participants in the Workshop on Atomic Experiments for Dark Matter and Gravity Exploration held at CERN: ({\tt https://indico.cern.ch/event/830432/}), as well as other interested scientists, and have incorporated additional material.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Terrestrial Very-Long-Baseline Atom Interferometry: summary of the second workshop

This summary of the second Terrestrial Very-Long-Baseline Atom Interferometry (TVLBAI) Workshop provides a comprehensive overview of our meeting held in London in April 2024 (Second Terrestrial Very-Long-Baseline Atom Interferometry Workshop, Imperial College, April 2024), building on the initial discussions during the inaugural workshop held at CERN in March 2023 (First Terrestrial Very-Long-Baseline Atom Interferometry Workshop, CERN, March 2023). Like the summary of the first workshop (Abend et al. in AVS Quantum Sci. 6:024701, 2024), this document records a critical milestone for the international atom interferometry community. It documents our concerted efforts to evaluate progress, address emerging challenges, and refine strategic directions for future large-scale atom interferometry projects. Our commitment to collaboration is manifested by the integration of diverse expertise and the coordination of international resources, all aimed at advancing the frontiers of atom interferometry physics and technology, as set out in a Memorandum of Understanding signed by over 50 institutions (Memorandum of Understanding for the Terrestrial Very Long Baseline Atom Interferometer Study).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Shell structure in 32P

The nuclear structure of 32P was investigated by detecting multi-γ coincidences along with charged light ions following the bombardment of an 18O target with a 30-MeV 16O beam from the Florida State University accelerator facility using the Clarion2-Trinity array of Clover γ spectrometers and GAGG (Gd-Al-Ga-garnet) scintillators for charged particles. A number of new states up to 12 MeV excitation and spins up to 9+ were observed by their γ decay patterns. Spins and parities were assigned by comparing measured γ angular distributions with polarizations inferred from Compton-scattering asymmetries between the Ge crystals in the Clover spectrometers. The new level scheme of 32P compares well with shell model calculations using the FSU cross-shell interaction and reasonably well with those using the sdpf-m interaction. In particular, structures with higher spin arise from promotion of more nucleons up to the f-p shell.

Allmond, James [ORNL] (ORCID:0000000165338721)↗

Visualizing Vehicle Acceleration and Braking Energy at Intersections along a Major Traffic Corridor

Automobiles approaching a controlled intersection need to brake and come to a full stop when the signal transitions from green to red, and the vehicle must later accelerate to normal speeds after the signal changes back to green. These stops and starts associated with normal signal changes lead to unnecessary energy consumption and vehicle emissions. Previous studies have revealed that the optimization of traffic intersections' signal controls and coordination facilitates smoother traffic flows with reduced stop-and-go driving, which can significantly reduce traffic congestion and unnecessary fuel waste. This paper presents an interactive visual analytics dashboard that allows transportation planners to explore and analyze energy consumption patterns resulting from temporally varying traffic signal phases at multiple intersections along a major transportation corridor using traffic simulation outputs. The visual dashboard is implemented as an accessible and responsive web application and employs a combination of visualization techniques to cover multiple aspects of vehicle acceleration and braking at multiple adjacent intersections along a corridor. The paper presents a case study of a simulated traffic scenario on the Shallowford Road traffic corridor located in Chattanooga, Tennessee to demonstrate the capability of the visual dashboard.

Xu, Haowen↗

Vibronic and Environmental Effects in Simulations of Optical Spectroscopy

Including both environmental and vibronic effects is important for accurate simulation of optical spectra, but combining these effects remains computationally challenging. We outline two approaches that consider both the explicit atomistic environment and the vibronic transitions. Both phenomena are responsible for spectral shapes in linear spectroscopy and the electronic evolution measured in nonlinear spectroscopy. The first approach utilizes snapshots of chromophore-environment configurations for which chromophore normal modes are determined. We outline various approximations for this static approach that assumes harmonic potentials and ignores dynamic system-environment coupling. The second approach obtains excitation energies for a series of time-correlated snapshots. This dynamic approach relies on the accurate truncation of the cumulant expansion but treats the dynamics of the chromophore and the environment on equal footing. Both approaches show significant potential for making strides toward more accurate optical spectroscopy simulations of complex condensed phase systems.

Chemistry↗

Anolyte Enhances Catalyst Utilization and Ion Transport Inside a CO 2 Electrolyzer Cathode

Electrochemical CO 2 reduction is a promising technology to capture and convert CO 2 to valuable chemicals. High Faradaic efficiencies of CO 2 reduction products are achieved with zero-gap alkaline CO 2 electrolyzers with a supporting electrolyte at the anode (anolyte). Herein, we investigate the effect of anolyte on the electrode properties such as catalyst utilization, ionic accessibility etc. of a CO 2 reduction cathode using electrochemical techniques and cell configurations that avoid the complexities related to co-electrolysis. Using 1M KOH as the anolyte and a Cu gas-diffusion-electrode with low Nafion content as the model CO 2 reduction electrode, we find that electrode capacitance (proxy for electrochemically active surface area) and ionic conductivity inside the cathode increase approximately 4 and 447 times, respectively, in presence of KOH. Liquid anolyte wets the electrode’s pore structure more efficiently than capillary condensation of feed water vapor. The ionomer coverage is very low, and its distribution inside the electrode is highly fragmented. Surface ion conduction mechanisms inside the electrode are orders of magnitude lower than the bulk ion conduction in presence of anolyte. This study shows that when an anolyte (e.g., KOH) is used, catalyst utilization and ionic accessibility inside the electrode increase significantly.

30 DIRECT ENERGY CONVERSION↗

Metabolomic and transcriptomic remodeling of bone marrow myeloid cells in response to maternal obesity

Maternal obesity puts the offspring at high risk of developing obesity and cardiometabolic diseases in adulthood. Here, we utilized a mouse model of maternal high-fat diet (HFD)-induced obesity that recapitulates metabolic perturbations seen in humans. We show increased adiposity in the offspring of HFD-fed mothers (Off-HFD) when compared with the offspring of regular diet-fed mothers (Off-RD). We have previously reported significant immune perturbations in the bone marrow of newly weaned Off-HFD. Here, we hypothesized that lipid metabolism is altered in the bone marrow of Off-HFD versus Off-RD. To test this hypothesis, we investigated the lipidomic profile of bone marrow cells collected from 3-week-old Off-RD and Off-HFD. Diacylglycerols (DAGs), triacylglycerols (TAGs), sphingolipids, and phospholipids were remarkably different between the groups, independent of fetal sex. Levels of cholesteryl esters were significantly decreased in Off-HFD, suggesting reduced delivery of cholesterol. These were accompanied by age-dependent progression of mitochondrial dysfunction in bone marrow cells. We subsequently isolated CD11b+ myeloid cells from 3-wk-old mice and conducted metabolomic, lipidomic, and transcriptomic analyses. The lipidomic profiles of myeloid cells were similar to those of bone marrow cells and included increases in DAGs and decreased TAGs. Transcriptomics revealed altered expression of genes related to immune pathways, including macrophage alternative activation, B-cell receptors, and transforming growth factor-β signaling. All told, this study revealed lipidomic, metabolomic, and gene expression abnormalities in bone marrow cells broadly, and in bone marrow myeloid cells particularly, in the newly weaned offspring of mothers with obesity, which might at least partially explain the progression of metabolic and cardiovascular diseases in their adulthood.

RNA sequencing↗

WaterTAP v1.0.0

WaterTAP is a new open source library of water-specific models built on the IDAES Integrated Platform to support the design and optimization of integrated water treatment systems, improve existing systems and enable the analysis of new designs incorporating emerging technologies. WaterTAP enables advanced modeling and optimization for: conceptual and multiscale design, dynamics and model predictive control of water systems and networks.

Beattie, KeithS↗

PFLOTRAN 5

PFLOTRAN leverages massively parallel, high performance computing to simulate large-scale non-isothermal multiphase flow, multicomponent reactive transport and electrical resistivity tomography (ERT) problems in the subsurface environment. Researchers have employed PFLOTRAN to simulate these Earth system processes on leadership class supercomputers for over two decades. The code is designed to predict the future estate of environmental systems and better inform stakeholders in the regulatory decision making process (e.g., fate of contaminants, long-term stewardship for nuclear waste, impact of climate change, etc.). A diverse team of scientists oversees PFLOTRAN development and maintenance under an open-source licensing agreement and manages contributions from an international community of researchers.

Hammond, Glenn↗

pnnl/MBDRL

Model-based Deep Reinforcement Learning for Real-time Grid Emergency Voltage Control. A model-based Deep Reinforcement Learning (DRL) framework where a deep neural network (DNN)-based surrogate model is utilized within the control policy learning framework, making the learning process faster and more sample efficient

Yin, Tim↗

Behind-the-meter Infrastructure Costs for Electrification Progression (BICEP) Model

The Behind-the-meter Infrastructure Costs for Electrification Progression (BICEP) model quantifies the behind-the-meter (BTM) electrical upgrades required for decarbonization through electrification by comparing the expected change in capacity requirements from the electrification technologies to the existing capacity in distributed energy resources (DER) stock (including buildings).

Yoder, Tim↗

ACAT

A Physics-Informed Machine Learning (PIML) framework for better system vulnerability assessment and faster corrective action recommendation. This framework consists of deriving physics-informed priors and smart sampling algorithms to help reduce the data samples of grid models and the dimension of simulation outputs, yielding small yet representative subset of the complex system, and both supervised and unsupervised machine learning (ML) algorithms for designing corrective actions

Chen, Yousu↗

C2QA/bosonic-qiskit

Extension of Qiskit to support hybrid boson-qubit simulations for the NQI C2QA effort.

Stavenger, Tim↗