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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

WE-G-BRD-09: Novel MRI Compatible Electron Accelerator for MRI-Linac Radiotherapy

Purpose: MRI guided radiotherapy is a rapidly growing field; however current linacs are not designed to operate in MRI fringe fields. As such, current MRI- Linac systems require magnetic shielding, impairing MR image quality and system flexibility. Here, we present a bespoke electron accelerator concept with robust operation in in-line magnetic fields. Methods: For in-line MRI-Linac systems, electron gun performance is the major constraint on accelerator performance. To overcome this, we propose placing a cathode directly within the first accelerating cavity. Such a configuration is used extensively in high energy particle physics, but not previously for radiotherapy. Benchmarked computational modelling (CST, Darmstadt, Germany) was employed to design and assess a 5.5 cell side coupled accelerator with a temperature limited thermionic cathode in the first accelerating cell. This simulation was coupled to magnetic fields from a 1T MRI model to assess robustness in magnetic fields for Source to Isocenter Distance between 1 and 2 meters. Performance was compared to a conventional electron gun based system in the same magnetic field. Results: A temperature limited cathode (work function 1.8eV, temperature 1245K, emission constant 60A/K/cm{sup 2}) will emit a mean current density of 24mA/mm{sup 2} (Richardson’s Law). We modeled a circular cathode with radius 2mm and mean current 300mA. Capture efficiency of the device was 43%, resulting in target current of 130 mA. The electron beam had a FWHM of 0.2mm, and mean energy of 5.9MeV (interquartile spread of 0.1MeV). Such an electron beam is suitable for radiotherapy, comparing favourably to conventional systems. This model was robust to operation the MRI fringe field, with a maximum current loss of 6% compared to 85% for the conventional system. Conclusion: The bespoke electron accelerator is robust to operation in in-line magnetic fields. This will enable MRI-Linacs with no accelerator magnetic shielding, and minimise painstaking optimisation of the MRI fringe field. This work was supported by US (NIH) and Australian (NHMRC & Cancer Institute NSW) government research funding. In addition, I would like to thank cancer institute NSW and the Ingham Institute for scholarship support.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Accelerated simulation of stochastic particle removal processes in particle-resolved aerosol models

Stochastic particle-resolved methods have proven useful for simulating multi-dimensional systems such as composition-resolved aerosol size distributions. While particle-resolved methods have substantial benefits for highly detailed simulations, these techniques suffer from high computational cost, motivating efforts to improve their algorithmic efficiency. Here we formulate an algorithm for accelerating particle removal processes by aggregating particles of similar size into bins. We present the Binned Algorithm for particle removal processes and analyze its performance with application to the atmospherically relevant process of aerosol dry deposition. We show that the Binned Algorithm can dramatically improve the efficiency of particle removals, particularly for low removal rates, and that computational cost is reduced without introducing additional error. In simulations of aerosol particle removal by dry deposition in atmospherically relevant conditions, we demonstrate about 50-times increase in algorithm efficiency.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Computational Capabilities for Predictions of Interactions at the Grain Boundary of Refractory Alloys

New high performance refractory alloys are critically required for improving efficiency and decreasing CO 2 emissions of fossil energy systems. The development of these materials remains slow because it is driven by a trial-and-error experimental approach and lacks a rational design approach. Atomistic Molecular Dynamic (MD) design has the potential to accelerate this development through the prediction of mechanical properties and corrosion resistance of new materials. The success of MD simulations depends critically on the fidelity of interatomic potentials. This project, in collaboration with Penn State, has focused on developing and validating high quality quantum mechanics based reactive potentials, ReaxFF, for Ni-Fe-Al-Cr-O-S system. A larger number of accurate density functional theory (DFT) calculations were performed to generate data for parameterizing the ReaxFF potentials. These potentials were then used in molecular dynamics (MD) and molecular dynamics-Monte Carlo (MD-MC) for much larger system to study for which DFT calculation would be prohibitively expensive, and to understand a number of chemical phenomena Ni-Fe-Al-Cr-O-S based alloy systems . These include catalytic oxidation of butane on clean Cr 2 O 3 and pyrite/Cr 2 O 3 , interfacial reaction between Cr 2 O 3 (refractory material) and Al 2 O 3 (slag), cohesive strength of at the grain boundary of S-enriched Cr compared to bulk Cr and Ssegregation study in Al, Al 2 O 3 , Cr and Cr 2 O 3 with a grain structure. The developed quantum based ReaxFF potential are available from the authors upon request. During this project, a number of papers were published in peer-reviewed journals. In addition, several conference presentations were made.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2014

Computational Capabilities for Predictions of Interactions at the Grain Boundary of Refractory Alloys

New high performance refractory alloys are critically required for improving efficiency and decreasing CO 2 emissions of fossil energy systems. The development of these materials remains slow because it is driven by a trial-and-error experimental approach and lacks a rational design approach. Atomistic Molecular Dynamic (MD) design has the potential to accelerate this development through the prediction of mechanical properties and corrosion resistance of new materials. The success of MD simulations depends critically on the fidelity of interatomic potentials. This project, in collaboration with Penn State, has focused on developing and validating high quality quantum mechanics based reactive potentials, ReaxFF, for Ni-Fe-Al-Cr-O-S system. A larger number of accurate density functional theory (DFT) calculations were performed to generate data for parameterizing the ReaxFF potentials. These potentials were then used in molecular dynamics (MD) and molecular dynamics-Monte Carlo (MD-MC) for much larger system to study for which DFT calculation would be prohibitively expensive, and to understand a number of chemical phenomena Ni-Fe-Al-Cr-O-S based alloy systems . These include catalytic oxidation of butane on clean Cr 2 O 3 and pyrite/Cr 2 O 3 , interfacial reaction between Cr 2 O 3 (refractory material) and Al 2 O 3 (slag), cohesive strength of at the grain boundary of S-enriched Cr compared to bulk Cr and Ssegregation study in Al, Al 2 O 3 , Cr and Cr 2 O 3 with a grain structure. The developed quantum based ReaxFF potential are available from the authors upon request. During this project, a number of papers were published in peer-reviewed journals. In addition, several conference presentations were made.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A computational investigation of high-flux, plate-and-frame membrane modules for industrial carbon capture

In this work, we study the application of membrane-based separation systems for carbon capture, considering plate-and-frame membrane modules. The successful deployment of membrane CO 2 capture system relies on high-performing membranes as well as effective membrane modules that can fully exploit the developed membranes. A plate-and-frame membrane module is especially attractive for CO 2 capture from industrial flue gas due to its lower pressure drop compared to its counterparts such as spiral wound modules and hollow fiber modules. To design better plate-and-frame modules, we investigate their basic unit - a single membrane stack through a combination of computational modeling and experimental investigations. The modeling approach is based on Computational Fluid Dynamics (CFD) to represent a multiphysics problem, including the fluid flow and diffusion processes within a membrane module. We use experimental data collected under different operating conditions to validate the CFD model. Numerical results suggest a good agreement between experiments and model outputs for the CO 2 recovery, CO 2 mole fraction in the retentate and permeate, and stage-cut. The CFD model is able to predict accurately the flow behavior, providing valuable insights on the effects of fluid dynamics on mass transfer of CO 2 . We also carry out a sensitivity analysis to identify the effect of key parameters on the CO 2 recovery and the CO 2 purity of the outlet streams.

CFD simulation↗
DOE OSTI2022

Numerical Investigation of the Spark Discharge Process in a Crossflow

The present study numerically investigates the spark discharge process under crossflow conditions using a thermal equilibrium plasma solver that fully couples the electromagnetic physics and fluid dynamics in a computational framework. Numerical results are validated by the comparison with experimental data. Here, the spark discharge experiment is performed in a constant volume vessel using an inductive coil ignition system for automotive applications, and the evolution of the spark channel is measured using high-speed imaging. The crossflow in the gap between the spark-plug electrodes is generated by a rotating fan with two different fan speeds, and the flow velocity across the gap is characterized by particle image velocimetry (PIV) measurement. A computational fluid dynamics (CFD) solver is employed to simulate the crossflow and provide the flow field variables (velocity, pressure, temperature) to the plasma solver. The crossflow velocity predicted in the flow simulation agrees well with the PIV data in that the non-uniform velocity profiles at monitoring points are reproduced by the CFD code. With the crossflow initialization in the plasma solver, the simulated spark discharge process from the breakdown to spark discharge matches the experimental data, including the voltage and circuit waveforms and the high-speed images of the spark channel evolution. The stretch of spark channel captured by plasma simulations agrees with the measured data. The plasma simulation reveals that the mean temperature of the spark channel is maintained at 5000 K during the discharge phase, and the temperature varies along the spark channel so that the highest value is obtained at the spark root on the center electrode. Overall, the results presented in this paper are meant to provide valuable information about the properties of the plasma generated by the spark discharge.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Network support for system initiated checkpoints

A system, method and computer program product for supporting system initiated checkpoints in parallel computing systems. The system and method generates selective control signals to perform checkpointing of system related data in presence of messaging activity associated with a user application running at the node. The checkpointing is initiated by the system such that checkpoint data of a plurality of network nodes may be obtained even in the presence of user applications running on highly parallel computers that include ongoing user messaging activity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Network support for system initiated checkpoints

A system, method and computer program product for supporting system initiated checkpoints in parallel computing systems. The system and method generates selective control signals to perform checkpointing of system related data in presence of messaging activity associated with a user application running at the node. The checkpointing is initiated by the system such that checkpoint data of a plurality of network nodes may be obtained even in the presence of user applications running on highly parallel computers that include ongoing user messaging activity.

Chen, Dong↗
DOE OSTI2024

Neutrons in Structural Biology: Challenges and Opportunities (Workshop Report)

Gaining a thorough understanding of biological systems requires building our knowledge about biological processes from the level of atoms and electrons, and up to whole organisms. Such comprehensive knowledge will allow for a predictive understanding of complex biological systems behavior. It will guide us in the design and development of novel therapeutics and vaccines to tackle existing health threats and to prepare for future pandemics, and it will provide information necessary to create new biomaterials and bio-inspired technologies through manipulation of biological macromolecules, their assemblies, single cells and even microorganisms. Reaching these goals will require a synergistic combination of multiple experimental techniques with molecular calculations and predictive simulations, and the design and development of new techniques and capabilities that bridge current knowledge and technology gaps. Neutron scattering provides unique information about the biomacromolecular structure and function and can play a major role in achieving these goals. A workshop was held to engage the scientific community in identifying pressing challenges in biochemistry, structural biology, enzymology and structure-guided drug design not solved with the current neutron scattering technologies or utilizing other structural biology techniques such as X-ray crystallography, NMR, and cryo-EM. The workshop brought together structural biology, biochemistry and computational experts, as well as early career researchers and students, creating a forum for discussing scientific advancement and collaboration. The workshop included a one-day satellite training workshop where graduate students and postdoctoral researchers were educated in the application of neutron crystallography and small-angle scattering in structural biology. Furthermore, the Instrument Scientific Advisory Board (ISAB) for the development of a macromolecular neutron diffractometer at ORNL’s Second Target Station was introduced at the workshop. The major outcome was that neutrons can provide atomic-level understanding of biomacromolecular structure, function and dynamics which is of paramount importance for addressing the identified challenges. Neutron crystallography, in particular, can resolve long-standing biochemical issues regarding enzyme function by delineating the underlying chemistry and can have a major impact on the design of small-molecule therapeutics, especially in combination with molecular computation (quantum chemistry and molecular dynamics simulations) and the emerging artificial intelligence (AI)-assisted drug design technologies. The unique properties of neutrons, including their high sensitivity to hydrogen and their non-destructive nature, make them ideal probes of biological matter. There is a palpable need in the scientific community to expand and enhance the impact of neutron sciences on biology. Neutron crystallography is the only structural biology method capable of determining positions of all hydrogen atoms in proteins, nucleic acids and their complexes at near-physiological temperatures and of unstable species at cryogenic temperatures. Moreover, neutron analysis is non-ionizing, non-destructive and does not perturb the structure or redox chemistry of active site metal centers and clusters in proteins, which can be invaluable for studying radiation-sensitive metalloprotein complexes. Further, neutron energies used in scattering applications are similar to atomic motions, permitting neutron spectroscopies to characterize the dynamics of biomacromolecules on the picosecond to microsecond timescales. The different sensitivities of neutrons to protium (H) and deuterium (D) isotopes of hydrogen allow enhanced visibility of specific parts of biological complexes through isotopic labeling. The impact of neutrons will be most powerful when neutron scattering is combined with complementary experimental techniques that use photons and electrons, and with high-performance computing. The interconnection and mutuality of the experimental and theoretical capabilities will drive discoveries in biological and health sciences to generate more complete picture of complex biological systems. The major limitation in the field of biological neutron crystallography has been signal-to-noise, demanding large samples that are difficult to produce for the majority of biomacromolecules and limiting the applicability of this technique in biological sciences. A neutron crystallography instrument at the Second Target Station will revolutionize biological science with neutrons by engaging a large scientific community of structural biologists, enabling successful neutron diffraction experiments from radically smaller biomacromolecular crystals, resolving unanswered biochemical questions, and meaningfully contributing to rational drug design. The meeting highlighted 10 grand challenges that will be addressed with this advanced capability over the next decade and beyond, and the recommendations required to help address them are given below.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Low-GWP HVAC System with Ultra-small Centrifugal Compression

Mechanical Solutions, Incorporated (MSI) was awarded a contract from the United States Department of Energy under Contract DE-EE0007042 to advance the potential of vapor compression utilizing an advanced high speed centrifugal compressor with an advanced heat exchanger design. The design was mandated to maintain high efficiency while utilizing a low GWP refrigerant. The specific goal of this program was to develop an advanced 5 ton air conditioning system. The target of the air conditioner is residential and commercial. To accomplish these goals, MSI teamed with Lennox International, a leading air conditioning manufacturer. MSI would design, oversee manufacturing, assemble, and test the compressor, while Lennox designed the heat exchanger and tested the overall air conditioner. Lennox initiated the project with a detailed cycle analysis that examined systems and refrigerants. At various break points, MSI performed a preliminary compressor design to identify realizable targets. Initially, the refrigerant that was targeted was R1234ze(E), but this was subsequently rejected over concerns of flammability. R515a was ultimately accepted as a qualified fluid based upon its GWP and flammability rating. MSI performed a complete design of the centrifugal compressor based upon the cycle system design and analysis. The design was based upon advanced aerodynamics utilizing transient Computational Fluid Dynamics (CFD), as well as mechanical and rotordynamic analysis. A detailed materials investigation was conducted to ensure mechanical integrity and refrigerant compatibility. To achieve the high rotational speed required by the compressor (105,300 rpm), foil bearings were designed by MSI, as was a high speed motor to provide the required torque for the compressor. All elements of the design complied with Design for Manufacturing and Assembly (DFMA) principles. The compressor was manufactured in components, utilizing specializing subcontractors throughout the country. The components were assembled into an operational compressor in MSI’s Albany facility, where it was tested in the MSI refrigeration test loop. The compressor achieved 90% of its maximum speed during testing at MSI. The interaction between the inverter and the high speed motor was the reason that full speed could not be attained. The compressor operated smoothly and quietly at all speeds, with the bearings performing as expected. The compressor was then shipped to Lennox’s facilities in Texas, where it was tested in the entire air conditioning system. Lennox was able to achieve 95% of the maximum rotational speed. They employed the same inverter as MSI. Lennox compiled the results of the testing and based upon the results, a go forward plan has been developed to correct the issues with the inverter, as well as redesign some parts that proved to be a challenge during the program. The consensus of the team is that a fully functional air conditioning system can be developed to achieve all of the goals identified in this program.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

DCDM1: Lessons Learned from the World's Most Energy Efficient Data Center

This presentation discusses the holistic approach to design the world's most energy-efficient data center, which is located at the U.S. Department of Energy National Renewable Energy Laboratory (NREL). This high-performance computing (HPC) data center has achieved a trailing twelve-month average power usage effectiveness (PUE) of 1.04 and features a chiller-less design, component-level warm-water liquid cooling, and waste heat capture and reuse. We provide details of the demonstrated PUE and energy reuse effectiveness (ERE) and lessons learned during four years of production operation. Recent efforts to dramatically reduce the water footprint will also be discussed. Johnson Controls partnered with NREL and Sandia National Laboratories to deploy a thermosyphon cooler (TSC) as a test bed at NREL's HPC data center that resulted in a 50% reduction in water usage during the first year of operation. The Thermosyphon Cooler Hybrid System (TCHS) integrates the control of a dry heat rejection device with an open cooling tower.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Mitigation of Cosmic Rays-Induced Errors in Superconducting Quantum Processors

Environmental radioactivity and cosmic-rays have recently been identified as a source of decoherence in super-conducting quantum bits (qubits). In particular, the absorption of cosmic-ray muons and gamma rays emitted by naturally occurring radioactive isotopes in the qubit substrate leads to correlated errors in superconducting quantum processors, posing significant challenges to quantum error correction. To enable quantum computing to scale, it is therefore necessary the devel-opment of mitigation strategies to prevent, or keep under control, error bursts due to particle impacts in the chip. While most environmental radioactive sources can be effectively suppressed using dedicated shielding, cosmic-ray muons, with their high penetration capability, can only be mitigated by moving the entire facility in a deep underground laboratory. This work explores the potential for developing a novel class of quantum processors equipped with an active veto system to protect superconducting-based quantum computers from the detrimental effects of atmospheric muons. Such a device would enable the identification of an atmospheric muon interaction within the processor and veto all operations performed during the occurrence of such an interaction. By demonstrating high detection efficiency and negligible dead time, we aim to establish that the future of quantum processors can be envisioned in above-around facilities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

GPU algorithms for Efficient Exascale Discretizations

In this paper we describe the research and development activities in the Center for Efficient Exascale Discretization within the US Exascale Computing Project, targeting state-of-the-art high-order finite-element algorithms for high-order applications on GPU-accelerated platforms. Furthermore, we discuss the GPU developments in several components of the CEED software stack, including the libCEED, MAGMA, MFEM, libParanumal, and Nek projects. We report performance and capability improvements in several CEED-enabled applications on both NVIDIA and AMD GPU systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

h5bench: A unified benchmark suite for evaluating HDF5 I/O performance on pre‐exascale platforms

Summary Parallel I/O is a critical technique for moving data between compute and storage subsystems of supercomputers. With massive amounts of data produced or consumed by compute nodes, high‐performant parallel I/O is essential. I/O benchmarks play an important role in this process; however, there is a scarcity of I/O benchmarks representative of current workloads on HPC systems. Toward creating representative I/O kernels from real‐world applications, we have created h5bench , a set of I/O kernels that exercise hierarchical data format version 5 (HDF5) I/O on parallel file systems in numerous dimensions. Our focus on HDF5 is due to the parallel I/O library's heavy usage in various scientific applications running on supercomputing systems. The various tests benchmarked in the h5bench suite include I/O operations (read and write), data locality (arrays of basic data types and arrays of structures), array dimensionality (one‐dimensional arrays, two‐dimensional meshes, three‐dimensional cubes), I/O modes (synchronous and asynchronous). In this paper, we present the observed performance of h5bench executed along several of these dimensions on existing supercomputers (Cori and Summit) and pre‐exascale platforms (Perlmutter, Theta, and Polaris). h5bench measurements can be used to identify performance bottlenecks and their root causes and evaluate I/O optimizations. As the I/O patterns of h5bench are diverse and capture the I/O behaviors of various HPC applications, this study will be helpful to the broader supercomputing and I/O community.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Real-Time GPU-Accelerated OFDR With an Integrated Auxiliary Interferometer

A GPU-accelerated optical frequency domain reflectometry (OFDR) system with an improved integrated auxiliary interferometer is proposed. Unlike conventional approaches that require separate auxiliary interferometers and multiple detection channels, the proposed OFDR system embeds this functionality directly into the signal via an intentional beat component. This enables self-calibration of laser nonlinearity while maintaining a cost-effective hardware configuration. Building on this simplified configuration, the system leverages GPU acceleration with an NVIDIA RTX 4070 Ti to achieve real-time performance, delivering high-throughput signal processing for continuous OFDR interrogation. The signal processing pipeline comprises signal capture, resampling for nonlinearity compensation, and frequency shift computation, all optimized for parallel execution. Hardware benchmarking demonstrates substantial acceleration over CPU implementations, achieving up to a 45× speedup for resampling and frequency shift computations and enabling processing latencies below 30 ms. Thermal response validation is conducted under two complementary scenarios: localized heating using a water bath and cryogenic-temperature conditions using liquid nitrogen. Under localized heating, the system achieves an accuracy of 0.249 °C with a thermal sensitivity of 5.971 GHz/°C, while cryogenic-temperature validation demonstrates a frequency shift response with a sensitivity of 2.383 GHz/°C and an accuracy of 2.04 °C. The high acceleration of the proposed GPU-accelerated OFDR system and its accuracy are achieved by exploiting CUDA-based stride indexing, enabling efficient parallel segmentation and processing of large datasets without additional memory copies. The benchmarking results confirm the robustness, accuracy, and deployability of the proposed OFDR system across a wide temperature range, establishing it as a practical platform for real-time distributed fiber sensing in structurally dynamic environments.

Harb, Salah [Lawrence Berkeley National Laboratory↗
DOE OSTI2018

DESIGN AND EXPERIMENTAL STUDY OF A HIGH PRESSURE AND SUPERCRITICAL METHANE-OXYGEN BURNER

Directly heated supercritical oxy-fuel power cycles have potential to offer a higher thermal efficiency and lower pollutant emissions compared to existing power cycles. Recent thermodynamic analysis of the cycle performed by several groups including the UTEP-Air Liquide research team show that combustion in the vicinity of 300 bar pressure and 1000-1400 K temperature allows for relatively high system efficiencies while operating within the limit of practical combustor materials. However, the realization of directly heated supercritical power cycle requires combustion systems be designed to operate in supercritical conditions and at temperature far below the blowout limit of conventional flames (above 1500 K), where not only the thermodynamic properties but also the combustion properties and kinetics are unexplored. To minimize these knowledge gaps, some intermediate pressure ranges (up to 20 bar) are experimented and modeled using a CFD simulation tool. The knowledge obtained from the high pressure test will assist in understanding the combustion chamber pressurization mechanism, ignition and flame behavior at the elevated pressure. This is a systematic first step in testing at higher pressures of 100 and 300 bar pressures. The primary objective of this dissertation is to perform qualitative analysis on oxy-methane combustion at high pressure (< 20 bar) and compare to CFD model for future scale up to supercritical condition. For modeling of the system, a commercial computational fluid dynamics simulation tool, ANSYS Fluent, is used. The inlet conditions for the CFD analysis are obtained from the experiments. The geometry used for the study is same as the test apparatus and operates at the same power ratings. The expertise gained from this experimental study is important to accurately and safely design combustors at elevated pressures up to 300bar. A high pressure methane-oxygen fuel burner and combustor have been developed to accommodate oxycombustion environment. A detailed CFD analysis is conducted to understand the flame length and cooling phenomenon inside the combustor first at pressures up to 20 bar to compare to experiments then at supercritical pressure. The first part of the dissertation compares CFD results with high pressure burner experiments at pressures up to 20 bar. The test is conducted for 30 s within 150 kW – 250 kW thermal power inputs. Afterwards, based on the simulation results a cooling system is proposed for steady state high pressure combustion experiments. It is observed from the experimental study that the proposed pressurization mechanism able to pressurize the vessel up to 20 bar. It is also determined that the current combustor can operate up to 20 bar for short term. The steady state CFD simulation demonstrates that a cooling system must be incorporated for continuous operation. Additionally, the study focuses on the ignition delay due to added diluent during the combustion process. It is observed that as the carbon dioxide recirculation ratio increases the ignition delay time increases. Later part of the dissertation provides a preliminary guideline for developing a laboratory scale supercritical oxy combustor. The employment of supercritical fluid in gas turbine is fairly a new concept. Hence, there are many questions that need to be answered. During this dissertation study an investigation is performed to understand the impact of equation of state in the supercritical combustion simulation. Finally, a CFD model for developing supercritical oxy-methane burner and the combustor, incorporating real gas model, is presented. Although Lee-Kesler equation of state provides better accuracy than Peng Robinson, due to the computational time Peng Robinson equation of state is used for the simulation. It is found that existing knowledge is not enough to simulate combustion at supercritical phase. Detailed combustion chemistry at the supercritical condition must be developed and should be incorporated to accurately replicate the combustion phenomenon.

Chowdhury, ASM Arifur Rahim↗
DOE OSTI2016

Energy scaling advantages of resistive memory crossbar based computation and its application to sparse coding

In this study, the exponential increase in data over the last decade presents a significant challenge to analytics efforts that seek to process and interpret such data for various applications. Neural-inspired computing approaches are being developed in order to leverage the computational properties of the analog, low-power data processing observed in biological systems. Analog resistive memory crossbars can perform a parallel read or a vector-matrix multiplication as well as a parallel write or a rank-1 update with high computational efficiency. For an N × N crossbar, these two kernels can be O(N) more energy efficient than a conventional digital memory-based architecture. If the read operation is noise limited, the energy to read a column can be independent of the crossbar size (O(1)). These two kernels form the basis of many neuromorphic algorithms such as image, text, and speech recognition. For instance, these kernels can be applied to a neural sparse coding algorithm to give an O(N) reduction in energy for the entire algorithm when run with finite precision. Sparse coding is a rich problem with a host of applications including computer vision, object tracking, and more generally unsupervised learning.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Xenon Recovery at Room Temperature using Metal-Organic Frameworks

Xenon is known to be a very efficient anesthetic gas but its cost prohibits the wider use in medical industry and other potential applications. It has been shown that Xe recovery and recycle from anesthetic gas mixture can significantly reduce its cost as anesthetic. The current technology uses series of adsorbent columns followed by low temperature distillation to recover Xe, which is expensive to use in medical facilities. Herein, we propose much efficient and simpler system to recover and recycle Xe from simulant exhale anesthetic gas mixture at room temperature using metal organic frameworks. Among the MOFs tested, PCN-12 exhibits unprecedented performance with high Xe capacity, Xe/N2 and Xe/O2 selectivity at room temperature. The in-situ synchrotron measurements suggest the Xe is occupied in the small pockets of PCN-12 compared to unsaturated metal centers (UMCs). Computational modeling of adsorption further supports our experimental observation of Xe binding sites in PCN-12.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗