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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A discretized representation for Monte Carlo simulation of deformed semiflexible chains

In this study, we present a novel orientation discretization approach based on the rhombic triacontahedron for Monte Carlo simulations of semiflexible polymer chains, aiming at enhancing structural analysis through rheo-small-angle scattering (rheo-SAS). Our approach provides a more accurate representation of the geometric features of semiflexible chains under deformation, surpassing the capabilities of traditional lattice structures. Validation against the Kratky–Porod chain system demonstrated superior consistency, underscoring its potential to significantly improve the precision of uncovering geometric details from rheo-SAS data. Further, this approach opens new avenues for investigating the conformations of semiflexible polymers and mechanically induced phase transitions in more complex polymer structures, offering deeper insights into their behavior under various conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2020

A Simulation Framework for Precision Landing and Hazard Avoidance Technology Assessments

To meet NASA’s challenge to return humans to the Moon in 2024 and establish a sustainable presence in 2028 requires advances in autonomous spacecraft navigation. The Safe and Precise Landing Integrated Capabilities Evolution (SPLICE) project, which leverages previous work at NASA to develop multi-mission precision landing and hazard avoidance technologies, is using a multi-faceted approach to achieve the advanced landing requirements. In addition to increasing the technology readiness level of key sensors and developing high performance space computing, SPLICE uses simulations to determine navigation requirements and evaluate sensor performance. The effort evaluates various precision landing concepts of operations, not only for the lunar human and robotic missions, but also for potential missions to other solar system destinations. This paper summarizes the six degree-of-freedom high fidelity simulation framework, trajectory design methodology, and sensor models being considered for a variety of precision lander missions. Initial results of the navigation sensor performance for a human Mars mission are presented. Finally, trade and sensitivity studies are outlined for future work to fully characterize sensor performance assumptions and modifications required to achieve precision landing and hazard avoidance.

Alicia Dwyer Cianciolo↗
DOE OSTI2023

Performance evaluation of cosmic ray muon trajectory estimation algorithms

Muons, being elementary particles with minimal interaction with nuclear materials and abundant at sea level, have sparked interest in utilizing them for imaging various applications, such as mining [Borselli et al., Sci. Rep. 12, 22329 (2022)], volcano imaging [Nagamine et al., Nucl. Instrum. Meth. A, 356, 585(1995)], and underground tunnel detection [Guardincerri et al., Pure Appl. Geophys. 174, 2133 (2017)]. Recently, their use in nuclear nonproliferation and safeguard verification has gained attention, particularly in cargo screening for nuclear waste smuggling [Baesso et al., J. Instrum. 9, C10041 (2014)], source localization [L. J. Schultz et al., Nucl. Instrum. Meth. A 519, 687 (2004)], and locating nuclear fuel debris in reactors [Borozdin et al., Phys. Rev. Let. 109, 152501 (2012)]. However, the resolution of muon image reconstruction techniques is limited due to multiple Coulomb scattering (MCS) within the target object. To achieve robust muon tomography, it is crucial to develop efficient and flexible physics-based algorithms that can model the MCS process accurately and estimate the most probable trajectory of muons as they pass through the target object. To address this limitation, in this study, a novel algorithmic approach utilizing the Bayesian probability theory and Gaussian approximation of MCS is chosen. Different energy levels, materials, and target sizes were considered in the evaluations. The results demonstrate that the Generalized Muon Trajectory Estimation (GMTE) algorithm offers significant improvements over currently used algorithms. Across all test scenarios, the GMTE algorithm demonstrated ~50% and 38% increase in precision compared to Straight Line Path (SLP) and Point of Closest Approach (PoCA) algorithms, respectively. Furthermore, it exhibited 10%–35% and 10%–15% increases in muon flux utilization for high and medium Z materials, respectively, compared to the PoCA algorithm. In conclusion, the extensive simulations confirm the enhanced performance and efficiency of the GMTE algorithm, offering improved resolution and reduced measurement time for cosmic ray muon imaging compared to the current SLP and PoCA algorithms.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Airborne hyperspectral imaging of nitrogen deficiency on crop traits and yield of maize by machine learning and radiative transfer modeling

Nitrogen is an essential nutrient that directly affects plant photosynthesis, crop yield, and biomass production for bioenergy crops, but excessive application of nitrogen fertilizers can cause environmental degradation. To achieve sustainable nitrogen fertilizer management for precision agriculture, there is an urgent need for nondestructive and high spatial resolution monitoring of crop nitrogen and its allocation to photosynthetic proteins as that changes over time. Here, we used visible to shortwave infrared (400–2400 nm) airborne hyperspectral imaging with high spatial (0.5 m) and spectral (3–5 nm) resolutions to accurately estimate critical crop traits, i.e., nitrogen, chlorophyll, and photosynthetic capacity (CO 2 -saturated photosynthesis rate, V max,27 ), at leaf and canopy scales, and to assess nitrogen deficiency on crop yield. We conducted three airborne campaigns over a maize (Zea mays L.) field during the growing season of 2019. Physically based soil-canopy Radiative Transfer Modeling (RTM) and data-driven approaches i.e. Partial-Least Squares Regression (PLSR) were used to retrieve crop traits from hyperspectral reflectance, with ground truth of leaf nitrogen, chlorophyll, V max,27 , Leaf Area Index (LAI), and harvested grain yield. To improve computational efficiency of RTMs, Random Forest (RF) was used to mimic RTM simulations to generate machine learning surrogate models RTM-RF. The results show that prior knowledge of soil background and leaf angle distribution can significantly reduce the ill-posed RTM retrieval. RTM-RF achieved a high accuracy to predict leaf chlorophyll content (R 2 = 0.73) and LAI (R 2 = 0.75). Meanwhile, PLSR exhibited better accuracy to predict leaf chlorophyll content (R 2 = 0.79), nitrogen concentration (R 2 = 0.83), nitrogen content (R 2 = 0.77), and V max,27 (R 2 = 0.69) but required measured traits for model training. We also found that canopy structure signals can enhance the use of spectral data to predict nitrogen related photosynthetic traits, as combining RTM-RF LAI and PLSR leaf traits well predicted canopy-level traits (leaf traits × LAI) including canopy chlorophyll (R 2 = 0.80), nitrogen (R 2 = 0.85) and V max,27 (R 2 = 0.82). Compared to leaf traits, we further found that canopy-level photosynthetic traits, particularly canopy V max,27 , have higher correlation with maize grain yield. This study highlights the potential for synergistic use of process-based and data-driven approaches of hyperspectral imaging to quantify crop traits that facilitate precision agricultural management to secure food and bioenergy production.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Energy-efficient, Large-scale Molecular Dynamics Simulations via Hardware- and Algorithm-level Optimization

This work aims to develop a framework for energy-efficient computing that will enable molecular dynamics (MD) simulations of large-scale phenomena with atomic precision and simultaneously remove computational bottlenecks limiting the speed of MD simulations. We seek to implement such an approach through the development of surrogate models for the interatomic force calculation combined with the use of mixed numerical precision formats. For a model system of neutral atoms (only pairwise interactions), significant force calculation efficiency improvements were achieved, without detrimental effects on atomic structures or average energies, using single precision, by developing a surrogate model (deep neural network), and by quantizing this surrogate model. For a model system of charged atoms, the reciprocal-space calculation of electrostatic interactions was identified as the main bottleneck, and the development of a surrogate model should be pursued to achieve an estimated one-order-of-magnitude additional speedup.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Mixed-precision iterative refinement using tensor cores on GPUs to accelerate solution of linear systems

Double-precision floating-point arithmetic (FP64) has been the de facto standard for engineering and scientific simulations for several decades. Problem complexity and the sheer volume of data coming from various instruments and sensors motivate researchers to mix and match various approaches to optimize compute resources, including different levels of floating-point precision. In recent years, machine learning has motivated hardware support for half-precision floating-point arithmetic. A primary challenge in high-performance computing is to leverage reduced-precision and mixed-precision hardware. We show how the FP16/FP32 Tensor Cores on NVIDIA GPUs can be exploited to accelerate the solution of linear systems of equations Ax = b without sacrificing numerical stability. The techniques we employ include multiprecision LU factorization, the preconditioned generalized minimal residual algorithm (GMRES), and scaling and auto-adaptive rounding to avoid overflow. We also show how to efficiently handle systems with multiple right-hand sides. On the NVIDIA Quadro GV100 (Volta) GPU, we achieve a 4×-5× performance increase and 5× better energy efficiency versus the standard FP64 implementation while maintaining an FP64 level of numerical stability.

GMRES↗
NASA NTRS2018

Spacecraft Alignment Determination and Control for Dual Spacecraft Precision Formation Flying

Many proposed formation flying missions seek to advance the state of the art in spacecraft science imaging by utilizing dual-spacecraft precision formation flying (PFF) to enable a 'virtual' telescope (VT). Using precision dual-spacecraft alignment, very long focal lengths can be achieved by locating the optics on one spacecraft and the detector on the other. Proposed science missions include astrophysics concepts for X-ray imaging and exo-planet observation with large spacecraft separations (1000 km to 80,000 km), and heliophysics concepts for X-ray or extreme ultra-violet (EUV) imaging or solar coronagraphs with smaller separations (50m - 500m). These proposed missions require advances in guidance, navigation, and control (GN&C) for PFF to enable high resolution science imaging. For many applications, the dual-spacecraft dynamics are coupled through the GN&C system when the relative ranging and position alignment sensor components are not co-located with their respective spacecraft mass centers. We develop a model-based PFF system design approach for the VT application, considering the coupling inherent in precision dual-spacecraft inertial alignment. These systems employ a variety of GN&C sensors and actuators, including laser-based alignment and ranging systems, camera-based imaging sensors, inertial measurement units (IMU), as well as microthruster systems and image motion compensation platforms. Results of a GN&C performance assessment reveal how data from relative position sensors can be employed in a Kalman filter framework to significantly improve alignment estimation performance. The assessment provides a comparison of two different GN&C formation flying architectures, illustrating the performance trades inherent in the choice of PFF system architecture in the VT application.

Formation Flying↗
DOE OSTI2025

First astrometric constraints on parity-violation in the gravitational wave background

Astrometry, the precise measurement of stellar positions and velocities, offers a promising approach to probing the low-frequency stochastic gravitational wave background (SGWB). Notably, astrometric vector sky maps are sensitive to parity-violating SGWB signals, which cannot be distinguished using pulsar timing array observations in an isotropic SGWB. We present the first astrometric constraints on parity-violating SGWB using quasar catalogs from Gaia DR3 and VLBA data. By analyzing the EB correlation in the two-point correlation function of the proper motions of the quasars, we find 2σ constraints on the parity-violating SGWB amplitude h 70 2 Ω V = -0.020 ± 0.025 from Gaia DR3 and h 70 2 Ω V = -0.004 ± 0.010 from VLBA. These constraints are valid in the frequency range 4.2 × 10 -18 Hz < f < 1.1 × 10 -8 Hz. Although not currently a tight constraint on theoretical models, this first attempt lays the groundwork for future investigations using more precise astrometric data.

Gravitational waves in GR and beyond: theory↗
DOE OSTI2021

Quantitative 2D thermometry in turbulent sooting non-premixed flames using filtered Rayleigh scattering

This paper demonstrates the application of a thermometry method in turbulent sooting non-premixed flames using filtered Rayleigh scattering (FRS). Fuel tailoring is used to establish a specific C 2 H 2 -based fuel mixture such that temperature can be determined accurately by a single FRS measurement over the entirety of mixture fraction space, or equivalently, for all relevant thermo-chemical states. Evaluation is performed in a hierarchy of flows to establish measurement precision and accuracy. Initial assessments in a series of heated fuel mixtures; non-sooting, near-adiabatic flat flames; and laminar non-premixed sooting flames show accuracy of the approach over a full range of expected temperatures and high single-shot measurement precision (e.g., 65 < <#comment/> S N R < <#comment/> 80 ) for temperatures between 1900 and 2200 K. Subsequently, 2D temperature measurements are evaluated in a turbulent non-premixed sooting flame. For the current fuel mixture, the local mixture-averaged Rayleigh scattering cross section is nearly constant over all composition space, and thus traditional laser Rayleigh scattering (LRS) is used as a measurement standard in the absence of soot. The results show excellent agreement between the proposed FRS thermometry approach and LRS in non-sooting regions. In the presence of soot, the proposed FRS-based approach shows no signs of interference. In addition, 2D temperature imaging shows high SNR (60–74) over all temperature conditions. Thus, we believe the proposed methodology successfully provides a high-resolution 2D temperature method under turbulent sooting flame conditions.

Pu, Jinpeng↗
DOE OSTI2020

Cryogenic single-molecule fluorescence annotations for electron tomography reveal in situ organization of key proteins in Caulobacter

Superresolution fluorescence microscopy and cryogenic electron tomography (CET) are powerful imaging methods for exploring the subcellular organization of biomolecules. Superresolution fluorescence microscopy based on covalent labeling highlights specific proteins and has sufficient sensitivity to observe single fluorescent molecules, but the reconstructions lack detailed cellular context. CET has molecular-scale resolution but lacks specific and nonperturbative intracellular labeling techniques. Here, we describe an imaging scheme that correlates cryogenic single-molecule fluorescence localizations with CET reconstructions. Our approach achieves single-molecule localizations with an average lateral precision of 9 nm, and a relative registration error between the set of localizations and CET reconstruction of ∼30 nm. We illustrate the workflow by annotating the positions of three proteins in the bacterium Caulobacter crescentus : McpA, PopZ, and SpmX. McpA, which forms a part of the chemoreceptor array, acts as a validation structure by being visible under both imaging modalities. In contrast, PopZ and SpmX cannot be directly identified in CET. While not directly discernable, PopZ fills a region at the cell poles that is devoid of electron-dense ribosomes. We annotate the position of PopZ with single-molecule localizations and confirm its position within the ribosome excluded region. We further use the locations of PopZ to provide context for localizations of SpmX, a low-copy integral membrane protein sequestered by PopZ as part of a signaling pathway that leads to an asymmetric cell division. Our correlative approach reveals that SpmX localizes along one side of the cell pole and its extent closely matches that of the PopZ region.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Growth Optimization and Device Integration of Narrow‐Bandgap Graphene Nanoribbons

Abstract The electronic, optical, and magnetic properties of graphene nanoribbons (GNRs) can be engineered by controlling their edge structure and width with atomic precision through bottom‐up fabrication based on molecular precursors. This approach offers a unique platform for all‐carbon electronic devices but requires careful optimization of the growth conditions to match structural requirements for successful device integration, with GNR length being the most critical parameter. In this work, the growth, characterization, and device integration of 5‐atom wide armchair GNRs (5‐AGNRs) are studied, which are expected to have an optimal bandgap as active material in switching devices. 5‐AGNRs are obtained via on‐surface synthesis under ultrahigh vacuum conditions from Br‐ and I‐substituted precursors. It is shown that the use of I‐substituted precursors and the optimization of the initial precursor coverage quintupled the average 5‐AGNR length. This significant length increase allowed the integration of 5‐AGNRs into devices and the realization of the first field‐effect transistor based on narrow bandgap AGNRs that shows switching behavior at room temperature. The study highlights that the optimized growth protocols can successfully bridge between the sub‐nanometer scale, where atomic precision is needed to control the electronic properties, and the scale of tens of nanometers relevant for successful device integration of GNRs.

36 MATERIALS SCIENCE↗
NASA NTRS2005

Technology-enabled Airborne Spacing and Merging

Over the last several decades, advances in airborne and groundside technologies have allowed the Air Traffic Service Provider (ATSP) to give safer and more efficient service, reduce workload and frequency congestion, and help accommodate a critically escalating traffic volume. These new technologies have included advanced radar displays, and data and communication automation to name a few. In step with such advances, NASA Langley is developing a precision spacing concept designed to increase runway throughput by enabling the flight crews to manage their inter-arrival spacing from TRACON entry to the runway threshold. This concept is being developed as part of NASA s Distributed Air/Ground Traffic Management (DAG-TM) project under the Advanced Air Transportation Technologies Program. Precision spacing is enabled by Automatic Dependent Surveillance-Broadcast (ADS-B), which provides air-to-air data exchange including position and velocity reports; real-time wind information and other necessary data. On the flight deck, a research prototype system called Airborne Merging and Spacing for Terminal Arrivals (AMSTAR) processes this information and provides speed guidance to the flight crew to achieve the desired inter-arrival spacing. AMSTAR is designed to support current ATC operations, provide operationally acceptable system-wide increases in approach spacing performance and increase runway throughput through system stability, predictability and precision spacing. This paper describes problems and costs associated with an imprecise arrival flow. It also discusses methods by which Air Traffic Controllers achieve and maintain an optimum interarrival interval, and explores means by which AMSTAR can assist in this pursuit. AMSTAR is an extension of NASA s previous work on in-trail spacing that was successfully demonstrated in a flight evaluation at Chicago O Hare International Airport in September 2002. In addition to providing for precision inter-arrival spacing, AMSTAR provides speed guidance for aircraft on converging routes to safely and smoothly merge onto a common approach. Much consideration has been given to working with operational conditions such as imperfect ADS-B data, wind prediction errors, changing winds, differing aircraft types and wake vortex separation requirements. A series of Monte Carlo simulations are planned for the spring and summer of 2004 at NASA Langley to further study the system behavior and performance under more operationally extreme and varying conditions. This will coincide with a human-in-the-loop study to investigate the flight crew interface, workload and acceptability.

Hull, James↗
NASA NTRS1982

Flight-test verification of a pictorial display for general aviation instrument approach

Results of flight tests of the pictorial "follow me" box display results of the simulator study. The most important item of agreement was the frequency of the vertical and lateral models of motion of the pilot-aircraft-display system, which was 0.4 rad/sec in each study. Successful short, curved, descending approaches, such as are often suggested for use with microwave landing systems, can be executed with the "follow me" box display. Variations of the value of distance from the aircraft to the box were also examined using values of 736 m, 368 m, and 184 m. The results show that successful approaches can be made with all of these values. A sharper final turn and greater precision of position control are obtained with the shorter distance. Deletion of distance measuring equipment from the system was also studies. It was shown that successful approaches can be made with no distance measures included in the system, but the values of distance from the aircraft to the box that can be used are restricted.

Adams, J. J.↗
NASA NTRS2006

Humanoid Mobile Manipulation Using Controller Refinement

An important class of mobile manipulation problems are move-to-grasp problems where a mobile robot must navigate to and pick up an object. One of the distinguishing features of this class of tasks is its coarse-to-fine structure. Near the beginning of the task, the robot can only sense the target object coarsely or indirectly and make gross motion toward the object. However, after the robot has located and approached the object, the robot must finely control its grasping contacts using precise visual and haptic feedback. This paper proposes that move-to-grasp problems are naturally solved by a sequence of controllers that iteratively refines what ultimately becomes the final solution. This paper introduces the notion of a refining sequence of controllers and characterizes this type of solution. The approach is demonstrated in a move-to-grasp task where Robonaut, the NASA/JSC dexterous humanoid, is mounted on a mobile base and navigates to and picks up a geological sample box. In a series of tests, it is shown that a refining sequence of controllers decreases variance in robot configuration relative to the sample box until a successful grasp has been achieved.

Platt, Robert↗
NASA NTRS2011

Reconfigurable Microwave Phase Delay Element for Frequency Reference and Phase-Shifter Applications

A technique was developed to provide a reconfigurable high-precision micro - wave electrical phase delay for resonators and phase shifters. The invention employs multiple branches of transmission lines with open-ended or ground-ended terminations as configurable bits or digits. This technique minimizes the errors due to limited precision of switching devices. In addition, the proposed linear analytical approach significantly produces a much simpler design than that of other prior inventions at the time of this reporting. Microwave components such as filters, phase delay elements, or resonators require a method that can accurately adjust their frequency responses. Most tuning techniques offer very wide frequency tuning range; however, it is often difficult and expensive to tune their response in a very narrow operating frequency, especially when the tuning element reaches its minimum discrete step due to fabrication tolerances. The problem becomes worse as the operating frequency is in mm-wave frequency range (>26 GHz). The electrical tuning sensitivity of a microwave line is dependent on the position of the tuning element with respect to the reference termination. By placing this tuning element away from this reference with the main transmission line connecting the two elements together the sensitivity of the tuning element can change significantly. This concept can be used in the system that requires multiple tuning sensitivities. In this case, multiple tuning branches are superimposed in the main transmission line. The proposed invention allows the transmission-line electrical length to be accurately programmed using switching elements that have limited accuracy. The invention consists of multiple branches of transmission lines connected to discrete switching devices with open-ended terminations. They are used as discrete tuning elements. These elements are connected to the main microwave transmission line and are separated by a well-defined electrical degree spacing. Each branch is programmed to have different electrical degree sensitivity, such as a combination of discrete steps in each branch, which results in a reflective line with a unique effective phase response. To reduce the number of switching devices, it is desirable to program the devices in binary configuration where each branch represents one bit in the base-2 number system. This invention allows the transmission line electrical length to be tuned precisely with customizable sensitivity based on the known sensitivity of the base tuning circuit. The tuning resolution is dependent on the distance among tuning branches.

Hsieh, Wen-Ting↗
DOE OSTI2020

Evaluating the exfoliation of two-dimensional materials with a Green's function surface model

Previous methods for the evaluation of the exfoliation of two-dimensional (2D) layered materials have drawbacks in computational efficiency and are unable to describe cases with semi-infinite substrates. Based on a Green's function surface (GFS) model, here we develop an approach to efficiently determine the tendency of exfoliation of 2D materials from their bulk crystals or semi-infinite substrates. By constructing appropriate surface configurations, we may calculate the exfoliation energy more precisely and quickly than the traditional way with the slab model. Furthermore, the GFS approach can provide angle-resolved photoemission spectroscopy of surface systems for direct comparison with experimental data. In this work, our findings indicate that the GFS approach is powerful for studies of 2D materials and various surface problems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2006

Humanoid Mobile Manipulation Using Controller Refinement

An important class of mobile manipulation problems are move-to-grasp problems where a mobile robot must navigate to and pick up an object. One of the distinguishing features of this class of tasks is its coarse-to-fine structure. Near the beginning of the task, the robot can only sense the target object coarsely or indirectly and make gross motion toward the object. However, after the robot has located and approached the object, the robot must finely control its grasping contacts using precise visual and haptic feedback. In this paper, it is proposed that move-to-grasp problems are naturally solved by a sequence of controllers that iteratively refines what ultimately becomes the final solution. This paper introduces the notion of a refining sequence of controllers and characterizes this type of solution. The approach is demonstrated in a move-to-grasp task where Robonaut, the NASA/JSC dexterous humanoid, is mounted on a mobile base and navigates to and picks up a geological sample box. In a series of tests, it is shown that a refining sequence of controllers decreases variance in robot configuration relative to the sample box until a successful grasp has been achieved.

Platt, Robert↗
DOE OSTI2025

Machine learning-driven predictive resource management in complex science workflows

Here, the collaborative efforts of large communities in science experiments, often comprising thousands of global members, reflect a monumental commitment to exploration and discovery. Recently, advanced and complex data processing has gained increasing importance in science experiments. Data processing workflows typically consist of multiple intricate steps, and the precise specification of resource requirements is crucial for each step to allocate optimal resources for effective processing. Estimating resource requirements in advance is challenging due to a wide range of analysis scenarios, varying skill levels among community members, and the continuously increasing spectrum of computing options. One practical approach to mitigate these challenges involves initially processing a subset of each step to measure precise resource utilization from actual processing profiles before completing the entire step. While this two-staged approach enables processing on optimal resources for most of the workflow, it has drawbacks such as initial inaccuracies leading to potential failures and suboptimal resource usage, along with overhead from waiting for initial processing completion, which is critical for fast-turnaround analyses. In this context, our study introduces a novel pipeline of machine learning models within a comprehensive workflow management system, the Production and Distributed Analysis (PanDA) system. These models employ advanced machine learning techniques to predict key resource requirements, overcoming challenges posed by limited upfront knowledge of characteristics at each step. Accurate forecasts of resource requirements enable informed and proactive decision-making in workflow management, enhancing the efficiency of handling diverse, complex workflows across heterogeneous resources.

97 MATHEMATICS AND COMPUTING↗