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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 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Limits to the Optical Response of Graphene and Two-Dimensional Materials

Two-dimensional (2D) materials provide a platform for strong light–matter interactions, creating wide-ranging design opportunities via new-material discoveries and new methods for geometrical structuring. Here we derive general upper bounds to the strength of such light–matter interactions, given only the optical conductivity of the material, including spatial nonlocality, and otherwise independent of shape and configuration. Our material figure-of-merit shows that highly doped graphene is an optimal material at infrared frequencies, whereas single-atomic-layer silver is optimal in the visible. For quantities ranging from absorption and scattering to near-field spontaneous-emission enhancements and radiative heat transfer, we consider canonical geometrical structures and show that in certain cases the bounds can be approached, while in others there may be significant opportunity for design improvement. The bounds can encourage systematic improvements in the design of ultrathin broadband absorbers, 2D antennas, and near-field energy harvesters.

2D materials↗
DOE OSTI2022

Multiplexed Anodic Stripping Voltammetry Detection of Heavy Metals in Water Using Nanocomposites Modified Screen-Printed Electrodes Integrated With a 3D-Printed Flow Cell

In this study, we present multiplexed anodic stripping voltammetry (ASV) detection of heavy metal ions (HMIs)—As(III), Cd(II), and Pb(II)—using a homemade electrochemical cell consisting of dual working, reference and counter screen-printed electrodes (SPE) on polyimide substrate integrated with a 3D-printed flow cell. Working and counter electrodes were fabricated by the screen-printing of graphite paste while the Ag/AgCl paste was screen-printed as a reference electrode (Ag/AgCl quasi-reference electrode). The working electrodes were modified with (BiO) 2 CO 3 -reduced graphene oxide (rGO)-Nafion [(BiO) 2 CO 3 -rGO-Nafion] and Fe 3 O 4 magnetic nanoparticles (Fe 3 O 4 MNPs) decorated Au nanoparticles (AuNPs)-ionic liquid (IL) (Fe 3 O 4 -Au-IL) nanocomposites separately to enhance HMIs sensing. Electrochemical detection was achieved using square wave ASV technique. The desired structure of the flow electrochemical cell was optimized by the computational fluid dynamic (CFD). Different experimental parameters for stripping analysis of HMIs were optimized including deposition time, deposition potential and flow rate. The linear range of calibration curves with the sensing nanocomposites modified SPE for the three metal ions was from 0–50 μg/L. The limits of detection (S/N = 3) were estimated to be 2.4 μg/L for As(III), 1.2 μg/L for Pb(II) and 0.8 μg/L for Cd(II). Furthermore, the homemade flow anodic stripping sensor platform was used to detect HMIs in simulated river water with a 95–101% recovery, indicating high selectivity and accuracy and great potential for applicability even in complex matrices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2005

Maintaining Situation Awareness with Autonomous Airborne Observation Platforms

Unmanned Aerial Vehicles (UAVs) offer tremendous potential as intelligence, surveillance and reconnaissance (ISR) platforms for early detection of security threats and for acquisition and maintenance of situation awareness in crisis conditions. However, using their capabilities effectively requires addressing a range of practical and theoretical problems. The paper will describe progress by the "Autonomous Rotorcraft Project," a collaborative effort between NASA and the U.S. Army to develop a practical, flexible capability for UAV-based ISR. Important facets of the project include optimization methods for allocating scarce aircraft resources to observe numerous, distinct sites of interest; intelligent flight automation software than integrates high-level plan generation capabilities with executive control, failure response and flight control functions; a system architecture supporting reconfiguration of onboard sensors to address different kinds of threats; and an advanced prototype vehicle designed to allow large-scale production at low cost. The paper will also address human interaction issues including an empirical method for determining how to allocate roles and responsibilities between flight automation and human operations.

Freed, Michael↗
DOE OSTI2019

Machine Learning Applied to a Variable Charge Atomistic Model for Cu/Hf Binary Alloy Oxide Heterostructures [Machine Learning a Variable Charge Atomistic Model for Cu/Hf Binary Alloy Oxide Heterostructures]

Alloy oxide heterostructures are essential for a wide variety of energy applications, including anticorrosion coatings, bifunctional catalysis, energy storage, as well as emerging platforms for multilevel nonvolatile memory and neuromorphic devices. The key role played by oxide composition, density, and stoichiometry in governing electrochemical reactions, interface structure, and ionic transport in alloy oxides remains largely unknown. This is primarily due to the lack of variable charge interatomic potential models that can adequately describe the various atomic/ionic interactions in alloy oxides within a unified framework. Here, we introduce a charge transfer ionic potential (CTIP) model for Cu/Hf/O alloy system and demonstrate its ability to accurately capture the complex potential energy surface owing to dynamically varying interactions, including metallic (Cu/Hf), ionic (Cu/Hf/Ox), mixed environment (interfaces). We leverage supervised machine learning methods powered by genetic algorithms coupled with local simplex optimization to efficiently navigate through a high-dimensional parameter space and identify an optimum set of an independent set of CTIP parameters. We train our model against an extensive first-principles based data set that includes lattice constants, cohesive energies, equations of state, and elastic constants of various experimentally observed polymorphs of hafnia, copper oxide, hafnium, as well as copper. Our machine-learned CTIP model captures the structure, elastic properties, thermodynamics, and energetic ordering of various polymorphs. It also accurately predicts the surface properties of both oxides and their metals. To demonstrate the suitability of our CTIP model for investigating dynamic processes, we employed it to identify the atomistic scale mechanisms associated with the initial nanoscale oxidation and surface oxide growth on Cu-doped hafnia surfaces. Here, our machine-learned CTIP model can be used to probe the dynamic response of Cu/Hf/O alloy interfaces subjected to external stimuli (e.g., electric field, pressure, temperature, strain, etc.) and a variety of atomistic phenomena including the dynamics of switching in emerging neuromorphic platforms.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Iodine-Containing Mass-Defect-Tuned Dendrimers for Use as Internal Mass Spectrometry Calibrants

Calibrants based on synthetic dendrimers have been recently proposed as a versatile alternative to peptides and proteins for both MALDI and ESI mass spectrometry calibration. Because of their modular synthetic platform, dendrimer calibrants are particularly amenable to tailoring for specific applications. Utilizing this versatility, a set of dendrimers has been designed as an internal calibrant with a tailored mass defect to differentiate them from the majority of natural peptide analytes. This was achieved by incorporating a tris-iodinated aromatic core as an initiator for the dendrimer synthesis, thereby affording multiple calibration points (m/z range 600–2300) with an optimized mass-defect offset relative to all peptides composed of the 20 most common proteinogenic amino acids. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

End-to-End Workflow for Machine-Learning-Based Qubit Readout With QICK and hls4ml

In this article, we present an end-to-end workflow for superconducting qubit readout that embeds codesigned neural networks into the quantum instrumentation control kit (QICK). Capitalizing on the custom firmware and software of the QICK platform, which is built on Xilinx radiofrequency system-on-chip field-programmable gate arrays (FPGAs), we aim to leverage machine learning (ML) to address critical challenges in qubit readout accuracy and scalability. The workflow utilizes the hls4ml package and employs quantization-aware training to translate ML models into hardware-efficient FPGA implementations via user-friendly Python application programming interfaces. We experimentally demonstrate the design, optimization, and integration of an ML algorithm for single transmon qubit readout, achieving 96% single-shot fidelity with a latency of 32.25 ns and less than 16% FPGA lookup table resource utilization. Our results offer the community an accessible workflow to advance ML-driven readout and adaptive control in quantum information processing applications.

42 ENGINEERING↗
DOE OSTI2021

Synchronous and Concurrent Multidomain Computing Method for Cloud Computing Platforms

We present a numerical method for synchronous and concurrent solution of transient elastodynamics problem where the computational domain is divided into subdomains that may reside on separate computational platforms. Here, this work employs the variational multiscale discontinuous Galerkin (VMDG) method to develop interdomain transmission conditions for transient problems. The fine-scale modeling concept leads to variationally consistent coupling terms at the common interfaces. The method admits a large class of time discretization schemes, and decoupling of the solution for each subdomain is achieved by selecting any explicit algorithm. Numerical tests with a manufactured solution problem show optimal convergence rates. The energy history in a free vibration problem is in agreement with that of the solution from a monolithic computational domain.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Data from Development of a CRISPR/Cas9-Based Tool for Gene Deletion in Issatchenkia orientalis

The nonconventional yeast Issatchenkia orientalis has emerged as a potential platform microorganism for production of organic acids due to its ability to grow robustly under highly acidic conditions. However, lack of efficient genetic tools remains a major bottleneck in metabolic engineering of this organism. Here we report that the autonomously replicating sequence (ARS) from Saccharomyces cerevisiae (ScARS) was functional for plasmid replication in I. orientalis , and the resulting episomal plasmid enabled efficient genome editing by the CRISPR/Cas9 system. The optimized CRISPR/Cas9-based system employed a fusion RPR1′-tRNA promoter for single guide RNA (sgRNA) expression and could attain greater than 97% gene disruption efficiency for various gene targets. Additionally, we demonstrated multiplexed gene deletion with disruption efficiencies of 90% and 47% for double gene and triple gene knockouts, respectively. This genome editing tool can be used for rapid strain development and metabolic engineering of this organism for production of biofuels and chemicals.

Conversion↗
DOE OSTI2022

Hydrogen Storage for Flexible Fossil Fuel Power Generation: Integration of Underground Hydrogen Storage with Gas Turbine (Final Report)

As the nation continues to encourage, through market structures and financial incentives, the proliferation of intermittent renewable electricity, how to optimize the ever-changing electric grid and identify means to retain and improve resilience, while ensuring continued reductions in GHG emissions, will be critical. According to Bloomberg, wind & solar generated 10.5% of US electricity in 2020 and that percentage continues to grow. In support of expanding renewable energy use, and to address its intermittent nature, this project will develop the Hydrogen Storage for Flexible Fossil Fuel Power Generation platform that is dispatchable, reliable, repeatable and have the ability to produce zero or negative carbon power while interfacing with geology capable of CO2 and hydrogen storage. GTI Energy (GTIE) and team members Illinois State Geological Survey (ISGS), Mitsubishi Heavy Industries America (MHIA), Ameren Illinois, Hexagon Purus, and the Low Carbon Resources Initiative (LCRI) completed a Phase I Conceptual Study under contract DE-FE0032012 for Hydrogen Storage for Flexible Fossil Fuel Power Generation: Integration of Underground Hydrogen Storage with Gas Turbine. The Hydrogen Storage for Flexible Fossil Fuel Power Generation platform addresses the intermittent nature of the expanding use of Variable Renewable Energy (VRE) generation. The low cost of the electricity (COE) generated results in greater dispatch and more operation at higher power levels (higher efficiency), fewer short intervals, and fewer start/stop cycles. The reliable, resilient system can produce zero carbon power and store hydrogen. It will demonstrate hydrogen storage in geologic formations like those used in natural gas underground storage thus enabling large scale storage of hydrogen in sedimentary strata across the United States rather than in geographically restricted salt caverns. The Phase I study confirmed the system is feasible and generates power at lower cost than other low carbon approaches. The demonstration defines the pathway for broad commercial application and will accelerate the development of larger systems suitable for centralized utility scale electricity production. The study advanced the maturity of the H 2 storage-based system with flexible power generation by completing a Pre-FEED study (Phase II). The Pre-FEED focused on the selected Energy Farm on the University of Illinois Urbana-Champaign (UIUC) site that includes above ground and underground hydrogen storage, low-carbon hydrogen production (GTI’s Compact Hydrogen Generator, CHG) with underground CO2 sequestration, and a 40-MW class gas turbine. The Pre-FEED addressed the entire system and its interconnection to the natural gas and electric grid and mitigation of key risks, such as storage behavior, load-following, and system operation. During Phase 1 of the project, the team completed key tasks, which moved the entire demonstration project, specific components and approaches closer to commercialization. These Phase I Accomplishments include: Completing System Requirements Review; Completing System Layout and Modeling - Heat & Mass Balance and Process Flow Diagram; Completing modelling of 9 turbine performance cases; Evaluating rock strata for underground storage of hydrogen and sequestration of carbon dioxide; Completing initial modelling of underground storage of hydrogen and withdrawal with evaluation of loss and water production; Identifying roadable storage for above ground hydrogen storage; Identifying existing electrical infrastructure for receiving/delivering electricity; Identifying existing gas supply infrastructure for receiving natural gas; Document concept design/development plans in required reports. Conclusions: The 12-month Feasibility study in Phase I study was completed and confirmed the system is feasible and generates power at lower cost than other low carbon approaches and even lower cost than the reference NGCC plant without carbon capture when taking advantage of 45Q carbon credits. The study enabled the fidelity of the concept to be improved and allowed identification of the requirements for the system. Defining the individual system and component requirements was performed via the system requirements review with the whole team. These requirements were then incorporated into and iterated with our Heat & Mass Balance process model and process flow diagrams were generated to reflect the overall system. This information was then used to complete the TEA and show economic feasibility. Large scale non-salt geologic storage of hydrogen is an enabling technology for a hydrogen-fired turbine that can be retrofitted into large-scale electric generating units (EGU). Our demonstration will include 428 MWh or ~4 hours full load of hydrogen storage (above and underground). Carbon capture inherent to the CHG process can capture 90% CO 2 (with upgrades to >98%). This system provides a COE of 23% savings relative to an NGCC with a post combustion amine system. Our proposed storage system decouples carbon capture and hydrogen production from power production; therefore, we expect our proposed system’s efficiency and variable COE to be superior resulting in overall higher dispatch and reduced deep cycling. Our demonstration will be full to multi-day hydrogen storage and has the potential for longer (seasonal) duration commercially. The demonstration defines the pathway for broad commercial application and will accelerate the development of larger systems suitable for centralized utility scale electricity production.

03 NATURAL GAS↗
DOE OSTI2020

Coordination Chemistry in the Structural and Functional Exploration of Actinide-Based Metal-Organic Frameworks

The coordination chemistry between inorganic and organic species can be optimally exemplified by metal–organic frameworks (MOFs), whose structures and functionalities can be rationally designed from these highly tunable building blocks. The high porosity, stability, and versatile functionalities of MOFs have attracted wide-spread attention from energy-related research and pollution remediation to biomedical applications. A unique and underexplored subset of these materials are MOFs based on actinide nodes; these MOFs have distinguished themselves as a unique platform for investigating the versatile oxidation states, reactivity, and coordination chemistry of actinides. Herein, we will focus on the rational design and synthesis of actinide-based MOFs under the general guidelines of coordination chemistry for their structural and functional explorations. The dimensionality, topology, and structures of actinide-based MOFs can be controlled by selecting pre-designed building blocks of actinide-based nodes and organic linkers with certain desired coordination geometries and functionalities. Furthermore, these unique actinide-based MOFs have shown promise for applications in nuclear waste mitigation, pollution control, and catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2011

Hayabusa Re-Entry: Trajectory Analysis and Observation Mission Design

On June 13th, 2010, the Hayabusa sample return capsule successfully re-entered Earth s atmosphere over the Woomera Prohibited Area in southern Australia in its quest to return fragments from the asteroid 1998 SF36 Itokawa . The sample return capsule entered at a super-orbital velocity of 12.04 km/sec (inertial), making it the second fastest human-made object to traverse the atmosphere. The NASA DC-8 airborne observatory was utilized as an instrument platform to record the luminous portion of the sample return capsule re-entry (~60 sec) with a variety of on-board spectroscopic imaging instruments. The predicted sample return capsule s entry state information at ~200 km altitude was propagated through the atmosphere to generate aerothermodynamic and trajectory data used for initial observation flight path design and planning. The DC- 8 flight path was designed by considering safety, optimal sample return capsule viewing geometry and aircraft capabilities in concert with key aerothermodynamic events along the predicted trajectory. Subsequent entry state vector updates provided by the Deep Space Network team at NASA s Jet Propulsion Laboratory were analyzed after the planned trajectory correction maneuvers to further refine the DC-8 observation flight path. Primary and alternate observation flight paths were generated during the mission planning phase which required coordination with Australian authorities for pre-mission approval. The final observation flight path was chosen based upon trade-offs between optimal viewing requirements, ground based observer locations (to facilitate post-flight trajectory reconstruction), predicted weather in the Woomera Prohibited Area and constraints imposed by flight path filing deadlines. To facilitate sample return capsule tracking by the instrument operators, a series of two racetrack flight path patterns were performed prior to the observation leg so the instruments could be pointed towards the region in the star background where the sample return capsule was expected to become visible. An overview of the design methodologies and trade-offs used in the Hayabusa re-entry observation campaign are presented.

Cassell, Alan M.↗
NASA NTRS2019

Design of Magnetic Shielding and Field Coils for a TES X-Ray Microcalorimeter Test Platform

The performance of transition-edge sensors (TES) and their SQUID multiplexed readouts is very sensitive to ambient magnetic field and its fluctuations. In order to run ground experiments on thousands of X-ray TES microcalorimeters with a small uniform ambient magnetic field (< 1 μT, with a uniformity < 0.1 μT), we need a very low ambient field to be trapped into the superconducting magnetic shields. We have designed a sub-Kelvin test platform to reach these specifications. For this purpose, we modeled a new design for the shielding consisting of a series of different mu-metal and superconducting shields, including a niobium shield at 50 mK, a cryoperm (A4K) shield at 3 K, and a mu-metal shield at 300 K. A magnetic field coil is used to vary the local perpendicular magnetic field over the TES array. To optimize this field, we have studied a number of different field-coil designs and the impact of the different shield geometries, in order to reach the required field uniformity.

Miniussi, Antoine R.↗
NASA NTRSDate not supplied

NASA’s WB-57F High Altitude Research Aircraft is Looking Up: A Flexible and Capable Heliophysics Platform for Coronal Observations During Total Solar Eclipses

NASA's WB-57F "Canberra" high altitude research aircraft is a unique airborne platform that serves a critical need in airborne science. Although the aircraft has been conventionally used for earth observation/remote sensing and in situ atmospheric sampling, research teams have begun to recognize the aircraft’s emerging role in heliophysics research. With the ability to operate at altitudes in excess of 60,000 feet and with a range of over 2,500 miles, the particular capabilities of the WB-57 are unparalleled by other aircraft in the government or commercial spaces. The Canberra has capacity to carry nearly 9,000 pounds of instrumentation across the aircraft, including modular payload areas in the belly, the nose, wing pods, and wing hatches. The WB-57 features a dedicated "person in the loop" sensor equipment operator, real-time high bandwidth data link between air and ground, and an on-board data network allowing interoperability between multiple systems and operator interfaces. The aircraft has a truly global reach, and has operated out of airfields all over the world with a minimal personnel footprint. The Program maintains a highly qualified engineering team that will work closely with customer requirements to optimize efficiency of payload installation and operation on the aircraft. NASA maintains its own airworthiness authority, allowing a bespoke "in house" approach to aircraft modifications and instrument integration. This often saves months of coordination and cost when compared with commercial options. On 8 April 2024, the WB-57 program executed a one-of-a-kind observation the corona over North America and provided a first-flight opportunity for several instruments that were historically strictly terrestrial. By integrating imagers, spectrometers, and ionosondes on the aircraft, research team partnerships with Southwest Research Institute, University of Hawai’i Institute for Astronomy, and Virginia Tech have demonstrated new and exciting applications for this venerable platform, were able to effectively eliminate the risk of adverse weather spoiling the data collection during totality, and reduce the amount of atmospheric interference in the collected spectral data.

Airborne Science↗
DOE OSTI2018

Cyberknife stereotactic radiosurgery and radiation therapy treatment planning system

CyberKnife is an image-guided stereotactical dose delivery system designed for both focal irradiation and radiation therapy (SRT). Focal irradiation refers the use of many small beams to deliver highly focus dose to a small target region in a few fractions. The system consists of a 6-MV linac mounted to a robotic arm, coupled with a digital x-ray imaging system. The radiation dose is delivered using many beams oriented at a number of defined or nodal positions around the patients. The CyberKnife can be used for both intracranial and extracranial treaments unlike the Gamma Knife which is limited to intracranial cases. Multiplan (Accuray Inc., Sunnyvale, CA) is the treatment planning system developed to cooperate with this accurate and versatile SRS and SRT system, and exploit the full function of Cyberknife in high-precision radiosurgery and therapy. Optimized inverse treatment plan can be achieved by fine-tuning contours and planning parameters. Precision is the newest version of Cyberknife treatment planning system (TPS) and an upgrade to Multiplan. It offers several new features such as Monte Carlo for multileaf collimator (MLC) and retreatment for other modalities that added more support for the Cyberknife system. The Cybeknife TPS is an easy-to-use and versatile inverse planning platform, suitable for stereotactic radiosurgery and radiation therapy. The knowledge and experience of the planner in this TPS is essential to improve the quality of patient care.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

A resettable in-line particle concentrator using AC electrokinetics for distributed monitoring of microalgae in source waters

Green algae have been studied as an important and effective biomarker to indicate water quality due to their sensitivity to toxic agents in freshwater sources. But, conventional methods to monitor algal physiology use a chlorophyll fluorometer whose use is hampered by high-cost, large footprint, and limited sensitivity for practical samples containing low algal concentration. In order to overcome these constraints, we developed a multi-level electrode platform for resettable trapping of algae via AC electro-osmosis (ACEO) and negative dielectrophoresis. Preliminary experiments were performed in freshwater with conductivity of 0.02 S/m. Algal trapping was demonstrated at a low voltage of 2 V. The concentration effect was experimentally verified by measuring the fluorescence intensity of algae and using hemocytometer counting chambers at the inlet and outlet of the multilevel microchannel lab-on-a-chip. An optimal frequency was found for trapping, which agrees with the frequency dependence of ACEO flow velocity. Through-flow rate and electrode dimensions were optimized as well. Trapping efficiencies within the range of 26% - 65% have been obtained. A maximum trapping rate of 182 cells/s was obtained with a flow rate of 20 l/min. Our lab-on-a-chip shows high potential for improving the limit of detection in algal monitoring and enabling the development of a portable, integrated and automated system for monitoring the quality of source drinking waters.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2024

An open-source data storage and visualization platform for collaborative qubit control

Developing collaborative research platforms for quantum bit control is crucial for driving innovation in the field, as they enable the exchange of ideas, data, and implementation to achieve more impactful outcomes. Furthermore, considering the high costs associated with quantum experimental setups, collaborative environments are vital for maximizing resource utilization efficiently. However, the lack of dedicated data management platforms presents a significant obstacle to progress, highlighting the necessity for essential assistive tools tailored for this purpose. Current qubit control systems are unable to handle complicated management of extensive calibration data and do not support effectively visualizing intricate quantum experiment outcomes. In this paper, we introduce Qubit Control Storage and Visualization ( QubiCSV ), a platform specifically designed to meet the demands of quantum computing research, focusing on the storage and analysis of calibration and characterization data in qubit control systems. As an open-source tool, QubiCSV facilitates efficient data management of quantum computing, providing data versioning capabilities for data storage and allowing researchers and programmers to interact with qubits in real time. The insightful visualization are developed to interpret complex quantum experiments and optimize qubit performance. QubiCSV not only streamlines the handling of qubit control system data but also improves the user experience with intuitive visualization features, making it a valuable asset for researchers in the quantum computing domain.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Design of Superconducting Optoelectronic Networks for Neuromorphic Computing

We have previously proposed a novel hardware platform (SOEN) for neuromorphic computing based on superconducting optoelectronics that presents many of the features necessary for information processing in the brain. Here we discuss the design and training of networks of neurons and synapses based on this technology. We present circuit models for the simplest neurons and synapses that we can use to build networks. We discuss the further abstracted integrate and fire model that we use for evolutionary optimization of small networks of these neurons. We show that we can use the TENNLab evolutionary optimization programming framework to design small networks for logic, control and classification tasks. We plan to use the results as feedback to inform our neuron design.

Buckley, Sonia↗
DOE OSTI2017

WARP

WARP, which can stand for ``Weaving All the Random Particles,'' is a three-dimensional (3D) continuous energy Monte Carlo neutron transport code developed at UC Berkeley to efficiently execute on NVIDIA graphics processing unit (GPU) platforms. WARP accelerates Monte Carlo simulations while preserving the benefits of using the Monte Carlo method, namely, that very few physical and geometrical simplifications are applied. WARP is able to calculate multiplication factors, neutron flux distributions (in both space and energy), and fission source distributions for time-independent neutron transport problems. It can run in both criticality or fixed source modes, but fixed source mode is currently not robust, optimized, or maintained in the newest version. WARP can transport neutrons in unrestricted arrangements of parallelepipeds, hexagonal prisms, cylinders, and spheres. The goal of developing WARP is to investigate algorithms that can grow into a full-featured, continuous energy, Monte Carlo neutron transport code that is accelerated by running on GPUs. The crux of the effort is to make Monte Carlo calculations faster while producing accurate results. Modern supercomputers are commonly being built with GPU coprocessor cards in their nodes to increase their computational efficiency and performance. GPUs execute efficiently on data-parallel problems, but most CPU codes, including those for Monte Carlo neutral particle transport, are predominantly task-parallel. WARP uses a data-parallel neutron transport algorithm to take advantage of the computing power GPUs offer.

Bergmann, RyanM. [University of California - Berke↗