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At least 1,207 records · Page 67

All sources NASA NTRS DOE OSTI

DOE OSTI2024

A fast and accurate domain decomposition nonlinear manifold reduced order model

Here, this paper integrates nonlinear-manifold reduced order models (NM-ROMs) with domain decomposition (DD). NM ROMs approximate the full order model (FOM) state in a nonlinear-manifold by training a shallow, sparse autoencoder using FOM snapshot data. These NM-ROMs can be advantageous over linear-subspace ROMs (LS-ROMs) for problems with slowly decaying Kolmogorov n-width. However, the number of NM-ROM parameters that need to be trained scales with the size of the FOM. Moreover, for “extreme-scale” problems, the storage of high-dimensional FOM snapshots alone can make ROM training expensive. To alleviate the training cost, this paper applies DD to the FOM, computes NM-ROMs on each subdomain, and couples them to obtain a global NM-ROM. This approach has several advantages: Subdomain NM-ROMs can be trained in parallel, involve fewer parameters to be trained than global NM-ROMs, require smaller subdomain FOM dimensional training data, and can be tailored to subdomain specific features of the FOM. The shallow, sparse architecture of the autoencoder used in each subdomain NM-ROM allows application of hyper-reduction (HR), reducing the complexity caused by nonlinearity and yielding computational speedup of the NM-ROM. This paper provides the first application of NM-ROM (with HR) to a DD problem. In particular, this paper details an algebraic DD reformulation of the FOM, training a NM-ROM with HR for each sub domain, and a sequential quadratic programming (SQP) solver to evaluate the coupled global NM-ROM. Theoretical convergence results for the SQP method and a priori and a posteriori error estimates for the DD NM-ROM with HR are provided. The proposed DD NM-ROM with HR approach is numerically compared to a DD LS-ROM with HR on the 2D steady-state Burgers’ equation, showing an order of magnitude improvement in accuracy of the proposed DD NM-ROM over the DD LS-ROM.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Decoding the protein–ligand interactions using parallel graph neural networks

Abstract Protein–ligand interactions (PLIs) are essential for biochemical functionality and their identification is crucial for estimating biophysical properties for rational therapeutic design. Currently, experimental characterization of these properties is the most accurate method, however, this is very time-consuming and labor-intensive. A number of computational methods have been developed in this context but most of the existing PLI prediction heavily depends on 2D protein sequence data. Here, we present a novel parallel graph neural network (GNN) to integrate knowledge representation and reasoning for PLI prediction to perform deep learning guided by expert knowledge and informed by 3D structural data. We develop two distinct GNN architectures: $$\hbox {GNN}_{\mathrm{F}}$$ GNN F is the base implementation that employs distinct featurization to enhance domain-awareness, while $$\hbox {GNN}_{\mathrm{P}}$$ GNN P is a novel implementation that can predict with no prior knowledge of the intermolecular interactions. The comprehensive evaluation demonstrated that GNN can successfully capture the binary interactions between ligand and protein’s 3D structure with 0.979 test accuracy for $$\hbox {GNN}_{\mathrm{F}}$$ GNN F and 0.958 for $$\hbox {GNN}_{\mathrm{P}}$$ GNN P for predicting activity of a protein–ligand complex. These models are further adapted for regression tasks to predict experimental binding affinities and $$\hbox {pIC}_{\mathrm{50}}$$ pIC 50 crucial for compound’s potency and efficacy. We achieve a Pearson correlation coefficient of 0.66 and 0.65 on experimental affinity and 0.50 and 0.51 on $$\hbox {pIC}_{\mathrm{50}}$$ pIC 50 with $$\hbox {GNN}_{\mathrm{F}}$$ GNN F and $$\hbox {GNN}_{\mathrm{P}}$$ GNN P , respectively, outperforming similar 2D sequence based models. Our method can serve as an interpretable and explainable artificial intelligence (AI) tool for predicted activity, potency, and biophysical properties of lead candidates. To this end, we show the utility of $$\hbox {GNN}_{\mathrm{P}}$$ GNN P on SARS-Cov-2 protein targets by screening a large compound library and comparing the prediction with the experimentally measured data.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Systematic Crosstalk Mitigation for Superconducting Qubits via Frequency-Aware Compilation

One of the key challenges in current Noisy Intermediate-Scale Quantum (NISQ) computers is to control a quantum system with high-fidelity quantum gates. There are many reasons a quantum gate can go wrong - for superconducting transmon qubits in particular, one major source of gate error is the unwanted crosstalk between neighboring qubits due to a phenomenon called frequency crowding. We motivate a systematic approach for understanding and mitigating the crosstalk noise when executing near-term quantum programs on superconducting NISQ computers. Here, we present a general software solution to alleviate frequency crowding by systematically tuning qubit frequencies according to input programs, trading parallelism for higher gate fidelity when necessary. The net result is that our work dramatically improves the crosstalk resilience of tunable-qubit, fixed-coupler hardware, matching or surpassing other more complex architectural designs such as tunable-coupler systems. On NISQ benchmarks, we improve worst-case program success rate by 13.3x on average, compared to existing traditional serialization strategies.

Computer architecture↗

NASA NTRS1988

The ijk forms of factorization methods. II - Parallel systems

The paper considers the 'ijk forms' of LU and Cholesky factorization on certain parallel computers. This extends an earlier analysis for vector computers. Attention is restricted to local memory systems with processors that may or may not have vector capability. Special attention is given to bus architectures but qualitative analyses are given for other interconnection systems.

Ortega, J. M.↗

NASA NTRS2015

Modular Stirling Radioisotope Generator

High efficiency radioisotope power generators will play an important role in future NASA space exploration missions. Stirling Radioisotope Generators (SRG) have been identified as a candidate generator technology capable of providing mission designers with an efficient, high specific power electrical generator. SRGs high conversion efficiency has the potential to extend the limited Pu-238 supply when compared with current Radioisotope Thermoelectric Generators (RTG). Due to budgetary constraints, the Advanced Stirling Radioisotope Generator (ASRG) was canceled in the fall of 2013. Over the past year a joint study by NASA and DOE called the Nuclear Power Assessment Study (NPAS) recommended that Stirling technologies continue to be explored. During the mission studies of the NPAS, spare SRGs were sometimes required to meet mission power system reliability requirements. This led to an additional mass penalty and increased isotope consumption levied on certain SRG-based missions. In an attempt to remove the spare power system, a new generator architecture is considered which could increase the reliability of a Stirling generator and provide a more fault-tolerant power system. This new generator called the Modular Stirling Radioisotope Generator (MSRG) employs multiple parallel Stirling convertor/controller strings, all of which share the heat from the General Purpose Heat Source (GPHS) modules. For this design, generators utilizing one to eight GPHS modules were analyzed, which provide about 50 to 450 watts DC to the spacecraft, respectively. Four Stirling convertors are arranged around each GPHS module resulting in from 4 to 32 Stirling/controller strings. The convertors are balanced either individually or in pairs, and are radiatively coupled to the GPHS modules. Heat is rejected through the housing/radiator which is similar in construction to the ASRG. Mass and power analysis for these systems indicate that specific power may be slightly lower than the ASRG and similar to the MMRTG. However, the reliability should be significantly increased compared to ASRG.

Stirling Cycle↗

NASA NTRS2016

Modular Stirling Radioisotope Generator

High-efficiency radioisotope power generators will play an important role in future NASA space exploration missions. Stirling Radioisotope Generators (SRGs) have been identified as a candidate generator technology capable of providing mission designers with an efficient, high-specific-power electrical generator. SRGs high conversion efficiency has the potential to extend the limited Pu-238 supply when compared with current Radioisotope Thermoelectric Generators (RTGs). Due to budgetary constraints, the Advanced Stirling Radioisotope Generator (ASRG) was canceled in the fall of 2013. Over the past year a joint study by NASA and the Department of Energy (DOE) called the Nuclear Power Assessment Study (NPAS) recommended that Stirling technologies continue to be explored. During the mission studies of the NPAS, spare SRGs were sometimes required to meet mission power system reliability requirements. This led to an additional mass penalty and increased isotope consumption levied on certain SRG-based missions. In an attempt to remove the spare power system, a new generator architecture is considered, which could increase the reliability of a Stirling generator and provide a more fault-tolerant power system. This new generator called the Modular Stirling Radioisotope Generator (MSRG) employs multiple parallel Stirling convertor/controller strings, all of which share the heat from the General Purpose Heat Source (GPHS) modules. For this design, generators utilizing one to eight GPHS modules were analyzed, which provided about 50 to 450 W of direct current (DC) to the spacecraft, respectively. Four Stirling convertors are arranged around each GPHS module resulting in from 4 to 32 Stirling/controller strings. The convertors are balanced either individually or in pairs, and are radiatively coupled to the GPHS modules. Heat is rejected through the housing/radiator, which is similar in construction to the ASRG. Mass and power analysis for these systems indicate that specific power may be slightly lower than the ASRG and similar to the Multi-Mission Radioisotope Thermoelectric Generator (MMRTG). However, the reliability should be significantly increased compared to ASRG.

Modules↗

NASA NTRS1993

Computer Electromagnetics and Supercomputer Architecture

The dramatic increase in performance over the last decade for microporcessor computations is compared with that for the supercomputer computations. This performance, the projected performance, and a number of other issues such as cost and the inherent pysical limitations in curent supercomputer technology have naturally led to parallel supercomputers and ensemble of interconnected microprocessors.

Electromagnetics Microprocessors Computers↗

NASA NTRS2005

Parallelization of Lower-Upper Symmetric Gauss-Seidel Method for Chemically Reacting Flow

Development of technologies for exploration of the solar system has revived an interest in computational simulation of chemically reacting flows since planetary probe vehicles exhibit non-equilibrium phenomena during the atmospheric entry of a planet or a moon as well as the reentry to the Earth. Stability in combustion is essential for new propulsion systems. Numerical solution of real-gas flows often increases computational work by an order-of-magnitude compared to perfect gas flow partly because of the increased complexity of equations to solve. Recently, as part of Project Columbia, NASA has integrated a cluster of interconnected SGI Altix systems to provide a ten-fold increase in current supercomputing capacity that includes an SGI Origin system. Both the new and existing machines are based on cache coherent non-uniform memory access architecture. Lower-Upper Symmetric Gauss-Seidel (LU-SGS) relaxation method has been implemented into both perfect and real gas flow codes including Real-Gas Aerodynamic Simulator (RGAS). However, the vectorized RGAS code runs inefficiently on cache-based shared-memory machines such as SGI system. Parallelization of a Gauss-Seidel method is nontrivial due to its sequential nature. The LU-SGS method has been vectorized on an oblique plane in INS3D-LU code that has been one of the base codes for NAS Parallel benchmarks. The oblique plane has been called a hyperplane by computer scientists. It is straightforward to parallelize a Gauss-Seidel method by partitioning the hyperplanes once they are formed. Another way of parallelization is to schedule processors like a pipeline using software. Both hyperplane and pipeline methods have been implemented using openMP directives. The present paper reports the performance of the parallelized RGAS code on SGI Origin and Altix systems.

Yoon, Seokkwan↗

DOE OSTI2025

Architecture-Dependent Thin Film Self-Assembly of Star Polystyrene-poly(2-vinylpyridine) Block Copolymers

Controlling the orientation of nanostructured block copolymer (BCP) thin films is essential for their use in templating, transport, and pattern transfer. Conventional efforts mainly focus on adjusting enthalpic interactions between the blocks and interfaces, while entropic contributions are often overlooked. Here, we show that the morphology of BCP thin films can be precisely tuned by the architectural design of star BCPs. Specifically, we synthesized multiarm star BCPs with a polystyrene (PS) core and poly(2-vinylpyridine) (P2VP) corona, which exhibits a lamellar microdomain morphology. The entropic penalty associated with a parallel orientation of the microdomains to the substrate is controlled by varying the number of arms comprising the star BCPs, from 2-arms (triblock) to 3-arms and 4-arms. We systematically investigated the thin film morphology at different depths using grazing incidence small-angle X-ray and neutron scattering (GISAXS and GISANS), atomic force microscopy (AFM), water contact angle (WCA), and interference microscopy. The results show that 2-arm star BCPs show a parallel orientation, the 3-arm star BCPs form a uniform PS film at the air surface with a vertical orientation of the microdomains underneath, and the 4-arm star BCPs exhibit a parallel microdomain orientation at the air surface with mixed parallel and perpendicular microdomain orientation in the bulk. Additionally, we found that the inclination angle of microdomains at the edges of islands and holes, resulting from the incommensurability between film thickness and the characteristic period of the microdomain morphology, increases with a higher number of arms. This suggests a greater grain boundary tilt angle in the microdomains of star-shaped block copolymers (BCPs). When silicon substrates were modified with PS homopolymer, the selective interaction between substrate and core blocks promotes a parallel orientation for the 4-arm star BCPs. In conclusion, this work shows that control of arm number in star BCPs affords diverse BCP thin film morphologies, offering insights into the star BCP conformations in thin films across different depths.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Cyber-Power Co-Simulation for End-to-End Synchrophasor Network Analysis and Applications

The resiliency, reliability and security of the next generation cyber-power smart grid depend upon efficiently leveraging advanced communication and computing technologies. Also, developing real-time data-driven applications is critical to enable wide-area monitoring and control of the cyber-power grid given high-resolution data from Phasor Measurement Units (PMUs). North American Synchrophasor Initiative Network (NASPlnet) provides guidance for PMU data exchanges. With the advancement in networking and grid operation, it is necessary to evaluate the performance of different data flow architectures suggested by NASPInet and analyze the impact on applications. Therefore, we need a cyber-power co-simulation framework that supports very large-scale co-simulation capable of running in parallel, high-performance computing platforms and capturing real-life network behavior. This work presents an end-to-end automated and user-driven cyber-power co-simulation using NS3 to model communication networks, GridPACK to model the power grid, and HELICS as a co-simulation engine. Comparative analysis of latency in synchrophasor networks and a performance evaluation of a power system stabilizer application utilizing PMU data in an IEEE 39 bus test system is presented using this cosimulation testbed.

Mustafa, Hussain M.↗

NASA NTRS2019

Towards Resilient Autonomous Navigation of Drones

Robots and particularly drones are especially useful in exploring extreme environments that pose hazards to humans. To ensure safe operations in these situations, usually perceptually degraded and without good GNSS, it is critical to have a reliable and robust state estimation solution. The main body of literature in robot state estimation focuses on developing complex algorithms favoring accuracy. Typically, these approaches rely on a strong underlying assumption: the main estimation engine will not fail during operation. In contrast, we propose an architecture that pursues robustness in state estimation by considering redundancy and heterogeneity in both sensing and estimation algorithms. The architecture is designed to expect and detect failures and adapt the behavior of the system to ensure safety. To this end, we present HeRO (Heterogeneous Redundant Odometry): a stack of estimation algorithms running in parallel supervised by a resiliency logic. This logic carries out three main functions: a) perform confidence tests both in data quality and algorithm health; b) re-initialize those algorithms that might be malfunctioning; c) generate a smooth state estimate by multiplexing the inputs based on their quality. The state and quality estimates are used by the guidance and control modules to adapt the mobility behaviors of the system. The validation and utility of the approach are shown with real experiments on a ying robot for the use case of autonomous exploration of subterranean environments, with particular results from the STIX event of the DARPA Subterranean Challenge.

Agha-mohammadi, Ali-akbar↗

DOE OSTI2022

Influence of weave architecture on mechanical response of SiC f -SiC m tubular composites

Due to their high resistance to radiation damage and elevated temperature, silicon carbide fiber-reinforced, silicon carbide matrix composites (SiC f -SiC m ) are identified as potential cladding structures for use in nuclear reactors. In this study, four composite architectures with varying ply numbers along the thickness direction and different biaxial or triaxial plain weave orientations at either 45° or 60°, were systematically evaluated under various stress states to assess the influence of weave architecture on mechanical performance. Experiments were conducted on SiC f -SiC m composite tubes under tensile hoop, axial compression, and rotating flexural loading to evaluate the mechanical response and investigate the failure modes using high-speed imaging and digital image correlation (DIC) techniques. It was found that for tensile hoop burst and flexural loading, the braiding angle had the most significant influence on the strength of the composite, whereas the effect of fiber angle was more limited for compression testing. Under axial compression a unique failure mode where a microcrack nucleates and grows only to a length equal to the thickness of a single yarn was identified. This crack growth behavior is reflected as periodic oscillations in the load-displacement response. For both axial and hoop loading, regardless of weave angle and number of plies, failure always initiated parallel to the tube axis in a single yarn and the cumulative interaction of these microcracks lead to either axial burst or fracture at an angle to the tube axis along a yarn. Furthermore, these results point to the importance of customizing the design of tube architecture for enhanced performance in specified nuclear applications.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Bayesian Optimization for Anything (BOA): An open-source framework for accessible, user-friendly Bayesian optimization

We introduce Bayesian Optimization for Anything (BOA), a high-level Bayesian Optimization (BO) framework and model wrapping toolkit, which presents a novel approach to simplifying BO, with the goal of making it more accessible and user-friendly, particularly for those with limited expertise in the field. BOA addresses common barriers in implementing BO, focusing on ease of use, reducing the need for deep domain knowledge, and cutting down on extensive coding requirements. A notable feature of BOA is its language-agnostic architecture, which facilitates broader application in various fields and to a wider audience. We showcase BOA's application through three examples: a high-dimensional optimization with parameters of the SWAT+ watershed model, a highly parallelized optimization of this intrinsically non-parallel model, and a multi-objective optimization of the FETCH Tree-Crown Hydrodynamics model. Furthermore, these test cases illustrate BOA's effectiveness in addressing complex optimization challenges in diverse scenarios.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

The Minos Computing Library: Efficient Parallel Programming for Extremely Heterogeneous Systems

Hardware specialization has become the silver bullet to achieve efficient high performance, from Systems-on-Chip systems, where hardware specialization can be ``extreme'', to large-scale HPC systems. As the complexity of the systems increases, so does the complexity of programming such architectures in a portable way. This work introduces the Minos Computing Library (MCL), as system software, programming model, and programming model runtime that facilitate programming extremely heterogeneous systems. MCL supports the execution of several multi-threaded applications within the same compute node, performs asynchronous execution of application tasks, efficiently balances computation across hardware resources, and provides performance portability. We show that code developed on a personal desktop automatically scales up to fully utilize powerful workstations with 8 GPUs and down to power-efficient embedded systems. MCL provides up to 17.5x speedup over OpenCL on NVIDIA DGX-1 systems and up to 1.88x speedup on single-GPU systems. In multi-application workloads, MCL dynamically resource allocation provides up to 2.43x performance improvement over manual, static allocation of computing resources.

Gioiosa, Roberto↗

NASA NTRS1979

The Massively Parallel Processor and its applications

A long-term experimental development program conducted at Goddard Space Flight Center to implement an ultrahigh-speed data processing system known as the Massively Parallel Processor (MPP) is described. The MPP is a single instruction multiple data stream computer designed to perform logical, integer, and floating point arithmetic operations on variable word length data. Information is presented on system architecture, the system configuration, the array unit architecture, individual processing units, and expected operating rates for several image processing applications (including the processing of Landsat data).

Strong, J. P.↗

NASA NTRS1990

Advanced software integration: The case for ITV facilities

The array of technologies and methodologies involved in the development and integration of avionics software has moved almost as rapidly as computer technology itself. Future avionics systems involve major advances and risks in the following areas: (1) Complexity; (2) Connectivity; (3) Security; (4) Duration; and (5) Software engineering. From an architectural standpoint, the systems will be much more distributed, involve session-based user interfaces, and have the layered architectures typified in the layers of abstraction concepts popular in networking. Typified in the NASA Space Station Freedom will be the highly distributed nature of software development itself. Systems composed of independent components developed in parallel must be bound by rigid standards and interfaces, the clean requirements and specifications. Avionics software provides a challenge in that it can not be flight tested until the first time it literally flies. It is the binding of requirements for such an integration environment into the advances and risks of future avionics systems that form the basis of the presented concept and the basic Integration, Test, and Verification concept within the development and integration life cycle of Space Station Mission and Avionics systems.

Garman, John R.↗

NASA NTRS1987

Spacelab Life Sciences flight experiments: an integrated approach to the study of cardiovascular deconditioning and orthostatic hypotension

The microgravity environment of spaceflight produces rapid cardiovascular changes which are adaptive and appropriate in that setting, but are associated with significant deconditioning and orthostatic hypotension on return to Earth's gravity. The rapidity with which these space flight induced changes appear and disappear provides an ideal model for studying the underlying pathophysiological mechanisms of deconditioning and orthostatic hypotension, regardless of etiology. Since significant deconditioning is seen after flights of very short duration, muscle atrophy due to inactivity plays, at most, a small role. These changes in circulatory control associated with cephalad fluid shifts, rather than inactivity per se, are probably more important factors. In order to test this hypothesis in a systematic way, a multidisciplinary approach which defines and integrates inputs and responses from a wide variety of circulatory sub-systems is required. The cardiovascular experiments selected for Spacelab Life Sciences flights 1 and 2 provide such an approach. Both human and animal models will be utilized. Pre- and post-flight characterization of the payload crew includes determination of maximal exercise capacity (bicycle ergometry), orthostatic tolerance (lower body negative pressure), alpha and beta adrenergic sensitivity (isoproterenol and phenylephrine infusions), baroreflex sensitivity (ECG-gated, stepwise changes in carotid artery transmural pressure with a pneumatic neck collar), and responses to a 24 h period of 5 deg head-down tilt. Measurements of cardiac output (CO2 and C2H2 rebreathing), cardiac chamber dimensions (phased-array 2-dimensional echocardiography), direct central venous pressure, leg volume (Thornton sock), limb blood flow and venous compliance (occlusion plethysmography), blood and plasma volumes, renal plasma flow and glomerular filtration rates, and various hormonal levels including catecholamines and atrial natriuretic factor will also be obtained. The central venous catheter will be inserted immediately pre-launch and monitored with heart rate and blood pressure in-flight until cardiac output, respiratory gas exchange and quantitative 2D echocardiography measurements can be performed. In-flight hemodynamic measurements will be repeated at rest and during submaximal exercise daily and also during maximal exercise midway through the flight to document the timecourse and extent of cardiovascular changes in the payload crew. Parallel studies are planned for the animals. In addition to measurements of right atrial and aortic pressures and cardiac output, a dorsal micro-circulatory chamber will allow determinations of changes in capillary and venular architecture and function in six of the rats. The techniques and findings from many of the SLS-1 and 2 supporting studies have already yielded significant information about circulatory regulation in patients with both hypo- and hypertension. The flight experiments themselves will provide new data to test the validity of both animal and human models currently used for simulating the fluid shifts of a micro-gravity environment. The development of effective countermeasures, not only for short and long duration space travellers, but also for Earth-bound medical patients can then be physiologically based on experimental data rather than anecdote.

Non-NASA Center↗

NASA NTRSDate not supplied

Rapid Lightweight Firmware Architecture of the Mobile Metamaterial Internal Co-Integrator Robot

The Mobile Metamaterial Internal Co-Integrator (MMIC-I) is a structure assembly and servicing robot for in-space servicing, assembly, and manufacturing of primary structures and infrastructure. MMIC-I is a battery-powered crawling robot that can travel through periodic structures such as trusses and open framework mechanical metamaterials. It does this through sequences of component extension, contraction, and gripping. This paper provides a detailed discussion of MMIC-I’s lightweight and rapidly developed firmware architecture, to enable demonstration of robot locomotion, secondary operations, and communications with a central command source. The rationale for the lightweight rapid development approach is to allow for assessment of long term system requirements in parallel with the mechatronics development, including optimization of system and subsystem power densities, to inform a future choice of flight ready software frameworks. MMIC-I system computing and I/O requirements are much lower than what is provided by proven baseline computing hardware for existing flight ready software frameworks such as the core Flight System, F prime, and the Robot Operating System. Development of earth gravity ground demonstration of the robotic systems is greatly benefited by limited power and mass factors for computing hardware. Here, we implement inter-process communication, commanding, and telemetry with the Espressif ESP32 module running the Arduino OS.

Damiana Catanoso↗