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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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NASA NTRS1994

Photovoltaic Power Conditioners: Development, Evolution, and the Next Generation

Market-place acceptance of utility-connected photovoltaic (PV) power generation systems and their accelerated installation into residential and commercial applications are heavily dependent upon the ability of their power conditioning subsystems (PCS) to meet high reliability, low cost, and high performance goals....This paper revisits past and present development efforts in PCS design, identifies the evolutionary improvements and describes the new opportunities for PCS designs...

solar↗
NASA NTRSDate not supplied

Statistical Engineering

This webinar provides an overview of the International Statistical Engineering Association (ISEA), and it illustrates the practice of statistical engineering at NASA. ISEA was formed to promote the study of how successful data-based problem-solving methods are leveraged to realize innovative opportunities and solve problems sustainably. ISEA is comprised of statisticians, engineers, scientists, and other professionals that exchange ideas and experiences in the development and application of statistical engineering theories. ISEA is building the body of knowledge of the statistical engineering discipline with a particular focus on improving academic preparation for tackling complex problems. Over the past 15 years, the practice of statistical engineering has gained recognition within NASA by spurring innovation and efficiency, and it has demonstrated significant impact. Aerospace research and development benefits from an application-focused statistical engineering perspective to accelerate learning, maximize knowledge, ensure strategic resource investment, and inform data-driven decisions. The second portion of this presentation provides an overview of infusing statistical engineering at NASA through pioneering case studies in aeronautics, space exploration, and atmospheric science.

Peter A Parker↗
NASA NTRS2022

Review of Solar Energetic Particle Models

Solar Energetic Particle (SEP) events are interesting from a scientific perspective as they are the product of a broad set of physical processes from the corona out through the extent of the heliosphere, and provide insight into processes of particle acceleration and transport that are widely applicable in astrophysics. From the operations perspective, SEP events pose a radiation hazard for aviation, electronics in space, and human space exploration, in particular for missions outside of the Earth’s protective magnetosphere including to the Moon and Mars. Thus, it is critical to improve the scientific understanding of SEP events and use this understanding to develop and improve SEP forecasting capabilities to support operations. Many SEP models exist or are in development using a wide variety of approaches and with differing goals. These include computationally intensive physics-based models, fast and light empirical models, machine learning-based models, and mixed-model approaches. The aim of this paper is to summarize all of the SEP models currently developed in the scientific community, including a description of model approach, inputs and outputs, free parameters, and any published validations or comparisons with data.

Kathryn Whitman↗
DOE OSTI2023

Non-Orthogonal Configuration Interaction for Fragments

An overview is given of the non-orthogonal configuration interaction (NOCI) implementation in the open-source program GronOR. After pointing out the specifics of NOCI and its extension to ensembles of molecules NOCI-Fragments (NOCI-F), the theoretical foundations of the approaches are described. The introduction of a common molecular orbital basis, the selection of the most contributing determinants pairs, and a massively parallel and GPU-accelerated implementation have made possible the application of NOCI to medium-sized systems as illustrated in a short overview of some of the recent applications.

de Graaf, C.↗
DOE OSTI2023

OpenACC Unified Programming Environment for Multi-hybrid Acceleration with GPU and FPGA

Accelerated computing in HPC such as with GPU, plays a central role in HPC nowadays. However, in some complicated applications with partially different performance behavior is hard to solve with a single type of accelerator where GPU is not the perfect solution in these cases. We are developing a framework and transpiler allowing the users to program the codes with a single notation of OpenACC to be compiled for multi-hybrid accelerators, named MHOAT (Multi-Hybrid OpenACC Translator) for HPC applications. MHOAT parses the original code with directives to identify the target accelerating devices, currently supporting NVIDIA GPU and Intel FPGA, dispatching these specific partial codes to background compilers such as NVIDIA HPC SDK for GPU and OpenARC research compiler for FPGA, then assembles binaries for the final object with FPGA bitstream file. In this paper, we present the concept, design, implementation, and performance evaluation of a practical astrophysics simulation code where we successfully enhanced the performance up to 10 times faster than the GPU-only solution.

Boku, Taisuke↗
DOE OSTI2026

Experimental longitudinal emittance manipulation using laser-based photoionization in the Fermilab Linac

A series of simulations and beam studies were conducted at Fermilab’s linear accelerator to evaluate the effectiveness of longitudinal emittance control via laser-induced photoionization. While similar laser techniques have been employed at Fermilab to enhance injection and extraction efficiency into the Booster, the work presented here focuses on extending these methods to bunch-by-bunch manipulation. This approach utilizes fine-scale correction of the H- bunches’ longitudinal spatial distribution. In theory, loosely confined particles in longitudinal phase space contribute to emittance growth during acceleration. By selectively removing these outlying particles through laser scraping (H- + γ → H + e-), this growth can be reduced. This report presents experimental results from both symmetric and asymmetric longitudinal scraping of H⁻ bunches in the Fermilab linac, which were subsequently injected into Booster, and evaluates the broader applicability of this method for future high-intensity accelerator operations.

Landon, Parker [Boston U.; Fermilab]↗
DOE OSTI2020

University Partnership Program for Scintillator Materials Research

The Scintillation Detection Development (SDD) group of the Particle Physics Division (PPD) at Fermi National Accelerator Laboratory (Fermilab) conducts research and development work in the field of materials that exhibit scintillation properties for use in particle detection and identification in nuclear and high energy physics experiments and applications. SDD has established a University Partnership Program for Scintillator Materials Research (Program), to facilitate collaboration with faculty and students from local universities. The collaboration between the SDD group and Dominican University will address the development of new plastic scintillating materials in two ways: 3.1. Synthesis of new organic fluorescent compounds to test with plastics commonly used in scintillation applications 3.2. Preparation and testing of commercially available plastics known for their resilience to radiation and rarely used in scintillation applications

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

FTTN: Feature-Targeted Testing for Numerical Properties of NVIDIA & AMD Matrix Accelerators

FTTN is a test suite to evaluate the numerical behaviors of matrix accelerators of GPUs (NVIDIA Tensor Cores and AMD Matrix Cores) in a quick and simple setting. Matrix accelerators are heavily used in today's computationally intense applications to speed up matrix multiplications. This test suite provides a comprehensive study on the numerical behaviors of these accelerators, including support for subnormals, rounding modes, extra precision bits and FMA features. Is there

Laguna Peralta, Ignacio↗
DOE OSTI2024

MLOps for Beam Controls

Machine learning operations (MLOps) is the standardization and streamlining of the ML development lifecycle to address the challenges associated with large-scale machine learning applications. The full MLOps pipeline consists of open-source tools: DataHub, MinIO and MLflow. It is being used for dataset management and model development to handle changing data dependencies, varying business needs, reproducibility, and diverse teams working with differing tools and skills. To demonstrate the completion of an MLOps pipeline for particle accelerator operations, we are deploying a simple script that computes settings for the Booster’s gradient magnet power supply. Once the demonstration is complete, we will develop and deploy ML-based optimization algorithms to improve Booster’s overall efficiency. This MLOps pipeline opens the gate to systematically develop and deploy ML applications for accelerator controls and diagnostics.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

MLOps for Beam Controls

Machine learning operations (MLOps) is the standardization and streamlining of the ML development lifecycle to address the challenges associated with large-scale machine learning applications. The full MLOps pipeline consists of open-source tools: DataHub, MinIO and MLflow. It is being used for dataset management and model development to handle changing data dependencies, varying business needs, reproducibility, and diverse teams working with differing tools and skills. To demonstrate the completion of an MLOps pipeline for particle accelerator operations, we are deploying a simple script that computes settings for the Booster’s gradient magnet power supply. Once the demonstration is complete, we will develop and deploy ML-based optimization algorithms to improve Booster’s overall efficiency. This MLOps pipeline opens the gate to systematically develop and deploy ML applications for accelerator controls and diagnostics.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

MLOps for Beam Controls

Machine learning operations (MLOps) is the standardization and streamlining of the ML development lifecycle to address the challenges associated with large-scale machine learning applications. The full MLOps pipeline consists of open-source tools: DataHub, MinIO and MLflow. It is being used for dataset management and model development to handle changing data dependencies, varying business needs, reproducibility, and diverse teams working with differing tools and skills. To demonstrate the completion of an MLOps pipeline for particle accelerator operations, we are deploying a simple script that computes settings for the Booster’s gradient magnet power supply. Once the demonstration is complete, we will develop and deploy ML-based optimization algorithms to improve Booster’s overall efficiency. This MLOps pipeline opens the gate to systematically develop and deploy ML applications for accelerator controls and diagnostics.

43 PARTICLE ACCELERATORS↗
NASA NTRS2000

A Tool for Automatic Data Distribution for CFD Applications on Structured Grids

Development of HPF versions of NPB and ARC3D has shown that HPF provides an efficient, concise way to express parallelism and to organize data traffic. The use of HPF, as noted in the papers, requires an intimate knowledge of the applications and a detailed analysis of data affinity, data movement, and data granularity. To simplify and accelerate the task of developing HPF versions of existing CFD applications we have designed and implemented ADAPT (Automatic Data Alignment and Placement Tool). ADAPT analyzes a CFD application working on a single structured grid and generates HPF TEMPLATE, (RE)DISTRIBUTION, ALIGNMENT, and INDEPENDENT directives. The directives can be generated on the nest level, subroutine level, application level, or on the application interface level. ADAPT annotates an existing CFD FORTRAN application, performing computations on single or multiple grids. On each grid the application is considered as a sequence of operators, each applied to a set of variables defined in a particular grid domain. ADAPT automatically detects implicit operators (i.e., having data dependences) and explicit operators (without data dependences). For parallelization of an explicit operator ADAPT creates a template for the operator domain, aligns arrays used in the operator with the template, distributes the template, and declares the loops over the distributed dimensions as INDEPENDENT. For parallelization of an implicit operator, the distribution of the operator's domain should be consistent with the operator's dependences. Any dependence between sections distributed on different processors would preclude parallelization if the compiler does not have an ability to pipeline computations. If a data distribution is "orthogonal" to the dependences of an implicit operator, then the loop which implements the operator can be declared as INDEPENDENT. ADAPT starts with an analysis of array index expressions of the loop nests. For each pair of arrays referenced in an assignment statement, it generates an arc in the alignment graph and annotates it with an affinity relation. The template, alignment, and distribution directives for a particular loop nest are then derived from a transitive closure of the affinity relation. A compromise of data distributions in different nests and subroutines is achieved by merging annotated alignment graphs for adjacent nests/stibroutine calls in the nest/call graph of the application in the process called distribution lifting. ADAPT has been implemented as a C++ program running in conjunction with a parallelization tool called CAPTools. ADAPT uses the parse tree, interprocedural analysis and application database generated by CAPTools. It also uses the Directed Graph class, initially implemented in p2d2 (parallel debugger oi distributed programs), and some other classes supporting symbolic computations. ADAPT uses data distribution techniques described. ADAPT was tested with ARC3D and the FT benchmark and has demonstrated a code performance within a factor of 1.5 of handwritten versions.

Frumkin, Michael↗
NASA NTRS1960

Landing Characteristics of a Reentry Capsule with a Torus-Shaped Air Bag for Load Alleviation

An experimental investigation has been made to determine the landing characteristics of a conical-shaped reentry capsule by using torus-shaped air bags for impact-load alleviation. An impact bag was attached below the large end of the capsule to absorb initial impact loads and a second bag was attached around the canister to absorb loads resulting from impact on the canister when the capsule overturned. A 1/6-scale dynamic model of the configuration was tested for nominal flight paths of 60 deg. and 90 deg. (vertical), a range of contact attitudes from -25 deg. to 30 deg., and a vertical contact velocity of 12.25 feet per second. Accelerations were measured along the X-axis (roll) and Z-axis (yaw) by accelerometers rigidly installed at the center of gravity of the model. Actual flight path, contact attitudes, and motions were determined from high-speed motion pictures. Landings were made on concrete and on water. The peak accelerations along the X-axis for landings on concrete were in the order of 3Og for a 0 deg. contact attitude. A horizontal velocity of 7 feet per second, corresponding to a flight path of 60 deg., had very little effect upon the peak accelerations obtained for landings on concrete. For contact attitudes of -25 deg. and 30 deg. the peak accelerations along the Z-axis were about +/- l5g, respectively. The peak accelerations measured for the water landings were about one-third lower than the peak accelerations measured for the landings on concrete. Assuming a rigid body, computations were made by using Newton's second law of motion and the force-stroke characteristics of the air bag to determine accelerations for a flight path of 90 deg. (vertical) and a contact attitude of 0 deg. The computed and experimental peak accelerations and strokes at peak acceleration were in good agreement for the model. The special scaling appears to be applicable for predicting full-scale time and stroke at peak acceleration for a landing on concrete from a 90 deg. flight path at a 0 deg. It appears that the full-scale approximately the same as those obtained from the model for the range of attitudes and flight paths investigated.

McGehee, John R.↗
DOE OSTI2026

Blueprint for DOE Quantum Supercomputing: Ensuring U.S. Leadership in the Quantum Decade

Quantum computing stands at the threshold of a transformative decade, where the field will evolve from small-scale demonstrations toward practical scientific computing at scale. This Blueprint identifies fault-tolerant quantum computers (FTQCs) as a viable, scalable, and broadly applicable path to achieving “quantum scientific utility,” defined as solving scientifically valuable problems beyond the reach of conventional, classical computers. This capability is expected to show scientific demonstrations in the late 2020s and to mature in the early-to-mid 2030s. This Blueprint outlines a strategy to prepare the U.S. Department of Energy (DOE) for FTQCs and their integration into the U.S. national scientific computing infrastructure. Its purpose is to identify the steps, milestones, and research directions necessary for DOE to enable initial deployment of FTQCs in 2028 as a scientific tool for the nation and mature this capability into the 2030s. DOE has a long history of supporting quantum information science and technology, contributing significantly to research advancements, training a quantum-ready workforce, and providing access to early small-scale quantum hardware. Given recent demonstrations of logical operations on error-corrected logical qubits and the advancement of commercial hardware roadmaps, DOE should begin preparations for large-scale, fault-tolerant quantum computing deployment for DOE science missions. This Blueprint proposes that DOE focus on (1) deploying first-generation scientifically relevant quantum computers with at least 100 logical qubits and performing at least 10,000 to 100,000 hard logical operations in scientifically relevant calculations; (2) developing essential FTQC programming competencies, system software, and facility readiness; and (3) investing in cutting edge focused R&D that fosters breakthroughs in scientific applications, algorithms, and logical architectures needed to accelerate the advent of scientific utility. This effort will position DOE to transition to larger systems: production-scale quantum computers that comprise 1,000 to 10,000 logical qubits, perform 1 to 10 billion hard logical operations, and execute scientifically useful computations at scale. Achieving these goals will require DOE facilities to evolve with urgency to support scientific campaigns that integrate quantum and classical computing resources into efficient workflows, novel software and firmware environments for compiling and routing quantum programs on FTQC machines, and suitable infrastructure for quantum hardware. It will also require further development and optimization of scientific applications from the fields of materials science, quantum chemistry, and high-energy and nuclear physics. The Blueprint calls for transformative R&D and collective action to accelerate the advent of scientific quantum utility and bring it within reach by 2028.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

LANSCE Overview for NA-113 WANDA 2022 [Slides]

Attached are presentation materials providing summary levels of LANSCE accelerator technical capabilities and experimental beam line applications with their associated user communities. These presentations are being provided as input material for the plenary session to be delivered by NA-113 at the WANDA 2022 meeting.

43 PARTICLE ACCELERATORS↗
NASA NTRS2012

Characterization of Tantalum Polymer Capacitors

Overview Reviewed data Caution must be taken when accelerating test conditions Data not useful to establish an acceleration model Introduction of new failure mechanism skewing results Evidence of Anti-Wear-Out De-doping of polymer Decreased capacitance Increased ESR Not dielectric breakdown Needs further investigation Further investigation into tantalum polymer capacitor technology Promising acceleration model for Manufacturer A Possibility for use in high-reliability space applications with suitable voltage derating.

Voltage Acceleration↗
DOE OSTI2026

Optical stochastic cooling at Fermilab’s IOTA ring

Stochastic cooling (SC) constitutes one of the greatest conceptual and technological achievements in particle beam cooling. Numerous SC systems have been built in the microwave regime and used to extend the science reach of accelerator facilities worldwide. The ability to sense and correct the particle ensemble using high-bandwidth feedback systems is at the core of the concept. Here, we describe the first realization of SC at optical frequencies and bandwidths. The demonstration was recently carried out at Fermilab’s integrable optics test accelerator (IOTA) storage ring using the transit-time method of optical stochastic cooling (OSC) and achieved an integrated system bandwidth of approximately 20 THz, which is more than 2000 times that of conventional SC systems. This demonstration establishes the foundation for more advanced OSC experiments with high-gain amplification, currently underway at Fermilab, and the eventual application of OSC to colliders and other accelerator facilities.

Jarvis, Jonathan D. [Fermilab]↗
NASA NTRS2018

Space-and Ground-Based Non-Accelerated Long Lifetime Data for Ruggedized Commercial Non-Planar Ring Oscillator (NPRO) Lasers

Lifetime data is presented for ruggedized commercial NPRO lasers used in the Tropospheric Emission Spectrometer (TES) Instrument on NASA’s Aura Earth-orbiting spacecraft, including 20 years of data from two life test units on the ground, 12 years of on-orbit data from TES Laser A, and 2 years of on-orbit data from TES Laser B. The TES lasers are diode-pumped Non-Planar Ring Oscillator (NPRO) lasers using Nd:YAG crystals. Since accelerated life testing was not possible on the complete laser, early prototype lasers that had gone through thermal cycling and vibration testing were placed on non-accelerated life tests with the hope of gathering at least a couple of years of data before launch. Long-term lifetime data for hybrid laser systems in space applications is not abundant, and out of necessity, accelerated reliability testing is usually done over a relatively short time with a large number of devices. The data presented in this paper is unique as it tracks the optical power output over time of a total of four lasers on the order of decades rather than months or years. Two of the lasers have each been on life test for over 20 years on the ground and are still operating, and the other two lasers have been on-orbit for 14 years. TES Laser A was still operating when the TES Instrument was decommissioned in January 2018. Therefore, the data presented covers over 450,000 non-accelerated device-hours, with 23% of those hours being in space.

Kane, T.J.↗