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At least 1,171 records · Page 65

Multi-state Catalysts Modulated by Mechanical Force (Final Report)

The development of more efficient catalytic processes and new approaches to control catalytic activity and selectivity are central to the realization of more selective, atom economic, and energy efficient routes to value added chemicals and polymers. The reactivity and selectivity of a transition metal catalyst is intimately related to the ligand-sphere geometry and, in many cases, the ideal ligand geometry for one step of a catalytic cycle is poorly matched to the ideal ligand geometry for another, resulting in sub-optimal efficiency. Macroscopic mechanical forces are both large, potentially much larger than interatomic forces, and are directional and localized to an extent that differentiates them from other forms of energy input such as heat or light. As such, mechanical force represents a heretofore untapped approach to modulate catalyst geometry, with the potential to reversibly modulate catalyst geometry on the timescale of catalytic turnover or monomer enchainment. This project has addressed the fundamental challenges in material-to-molecule strain coupling associated with the development of a new class of mechanically responsive catalysts (mechanocatalysts) in which active organotransition metal catalysts are strategically embedded in a flexible polymer network such that application of external mechanical force (stretching or deformation) leads to modulation of catalyst geometry, and hence reactivity and selectivity. Our efforts during the tenure of this grant were directed toward the elucidation of force-reactivity relationships of elementary transformations that occur within the first coordination sphere of a transition metal complex employing stiff stilbene photoswitches tethered to a flexible bidentate phosphine ligand derived from MeOBiphep as molecular force probes which provide a range of compressive and extension forces to the coupled transition metal complex depending on the geometry of the stiff stilbene and length of the tethering chains. During the tenure of this grant, we have quantified the rate of C(sp 2 )-C(sp 2 ) reductive elimination from platinum(II) diaryl complexes containing bis(phosphine) force probe ligands as a function of mechanical force; compressive forces decreased the rate of reductive elimination whereas extension forces increased the rate relative to the strain-free MeOBiphep complex with a 3.4-fold change in rate over a ~290 pN range of restoring forces. In a similar manner, we have quantified the rate of oxidative addition of bromobenzene to low-ligated palladium(0) complexes containing force probe ligands as a function of mechanical force; compressive forces increase the rate of oxidative addition, whereas tensile forces decrease the rate with a ~6 fold change in rate across ~340 pN of force applied to the complexes. In both cases, experimental and computational analyses argue strongly against any significant force-induced perturbation of ground state geometry within the first coordination sphere of the reactant complexes. Rather, the force/rate behavior observed for these transformations across these ranges of forces is attributed to the coupling of force to the nuclear motion comprising the reaction coordinates for reductive elimination and oxidative addition. These results together inform the development of catalysts whose activity can be tuned by an external force that is adjusted within a catalytic cycle and suggest opportunities to experimentally map geometry changes associated with reactions in transition metal complexes and potential strategies for force-modulated catalysis.

99 GENERAL AND MISCELLANEOUS↗

Finite-Temperature Structures of Supported Subnanometer Catalysts Inferred via Statistical Learning and Genetic Algorithm-Based Optimization

Single-atom catalysts (SACs) minimize noble metal utilization and can alter the activity and selectivity of supported metal nanoparticles. However, the morphology of active centers, including single atoms and subnanometer clusters of a few atoms, remains elusive due to experimental challenges. The computational cost to describe numerous cluster shapes and sizes makes direct first-principles calculations impractical. We present a computational framework to enable structure determination for single-atom and subnanometer cluster catalysts. As a case study, we obtained the low energy structures of Pd n (n = 1-21) clusters supported on CeO 2 (111), which are critical components of automobile three-way catalysts. Trained on density functional theory data, a three-dimensional cluster expansion is established using statistical learning to describe the Hamiltonian and predict energies of supported Pdn clusters of any structure. Low energy stable and metastable structures are identified using a Metropolis Monte Carlo-based genetic algorithm in the canonical ensemble at 300 K. We observe that supported single atoms sinter to form bilayer clusters and large cluster isomers share similarities in both shape and energy, and elucidate the significance of the support and microstructure on cluster stability. We discovered a simple surrogate structure-energy model, where the energy per atom scales with the square root of the average first coordination number, which can be used to estimate energies and compare the stability of clusters. Our framework, applicable to any metal/support system, fills an important methodological gap to predict the stability of supported metal catalysts in the subnanometer regime.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The HYTHIRM Project: Flight Thermography of the Space Shuttle During the Hypersonic Re-entry

This report describes a NASA Langley led endeavor sponsored by the NASA Engineering Safety Center, the Space Shuttle Program Office and the NASA Aeronautics Research Mission Directorate to demonstrate a quantitative thermal imaging capability. A background and an overview of several multidisciplinary efforts that culminated in the acquisition of high resolution calibrated infrared imagery of the Space Shuttle during hypervelocity atmospheric entry is presented. The successful collection of thermal data has demonstrated the feasibility of obtaining remote high-resolution infrared imagery during hypersonic flight for the accurate measurement of surface temperature. To maximize science and engineering return, the acquisition of quantitative thermal imagery and capability demonstration was targeted towards three recent Shuttle flights - two of which involved flight experiments flown on Discovery. In coordination with these two Shuttle flight experiments, a US Navy NP-3D aircraft was flown between 26-41 nautical miles below Discovery and remotely monitored surface temperature of the Orbiter at Mach 8.4 (STS-119) and Mach 14.7 (STS-128) using a long-range infrared optical package referred to as Cast Glance. This same Navy aircraft successfully monitored the Orbiter Atlantis traveling at approximately Mach 14.3 during its return from the successful Hubble repair mission (STS-125). The purpose of this paper is to describe the systematic approach used by the Hypersonic Thermodynamic Infrared Measurements team to develop and implement a set of mission planning tools designed to establish confidence in the ability of an imaging platform to reliably acquire, track and return global quantitative surface temperatures of the Shuttle during entry. The mission planning tools included a pre-flight capability to predict the infrared signature of the Shuttle. Such tools permitted optimization of the hardware configuration to increase signal-to-noise and to maximize the available dynamic range while mitigating the potential for saturation. Post flight, analysis tools were used to assess atmospheric effects and to convert the 2-D intensity images to 3-D temperature maps of the windward surface. Comparison of the spatially resolved global thermal measurements to surface thermocouples and CFD prediction is made. Successful demonstration of a quantitative, spatially resolved, global temperature measurement on the Shuttle suggests future applications towards hypersonic flight test programs within NASA, DoD and DARPA along with flight test opportunities supporting NASA's project Constellation.

Horvath, Thomas J.↗

Gateway Autonomy for Enabling Deep Space Exploration

The Gateway spacecraft is an important stepping-stone to exploration of the solar system, integrating commercial and international partners into a tightly coupled system, enabling cislunar activities, and implementing key technologies for missions to Mars. Autonomy is a capability area necessary to handle long communication outages where intervention from Earth is impossible, to prepare to operate with long communication delays that will be common in interplanetary travel, and to make spaceflight more affordable and accessible by reducing sustaining operations costs. The Gateway Concept of Operations states that one of Gateway’s goals is to “focus on infrastructure and systems that will allow autonomous operations aboard the Gateway with robotics, automated systems, advanced communications, and distributed computing.” Gateway’s Vehicle Systems Manager (VSM) and associated Autonomous Spacecraft Management Architecture (ASMA) are key products towards delivering autonomous capability. The primary functions of the control architecture are Mission Management and Timeline Execution, Resource Management, Fault Management, and Vehicle Control and Operation (VCO). In each of these areas, there is an initial level of capability to be delivered at launch, with plans to continue development and grow to greater capability. The initial deployment of VSM will focus on maintaining vehicle safety by focusing on full fault management capabilities and deploying only enough resource and timeline planning functionality to support that. The final deployment of VSM will add significant planning and control optimization functionality to support nominal operations for up to 21 days without ground support, even accommodating fault and failure conditions. While the VSM is the vehicle-level representation of autonomous reasoning, distributed automation is essential to provide the right scope and abstraction of information to process. Module and system support of automation and simplicity of interfaces are two important design paradigms that Gateway is focusing on to garner a systems approach to autonomy. Distribution of reasoning can increase complexity, so Gateway is also taking a strict hierarchical approach to information flow and decision making. VSM is not the only capability necessary to achieve an autonomous spacecraft. Robotics support for maintenance of the spacecraft will be essential to provide continued vehicle functionality even when crew is not present. Technical and programmatic challenges exist when implementing autonomous robotics operations. These challenges include sufficient network flexibility to support data transfer to the rest of the vehicle to coordinate module-to-module robotic walk-offs and finding the proper interfaces to allow sufficient dexterity. Communication system upgrades planned for Gateway include Delay Tolerant Networking to best utilize the complex network of relays that will be part of mature cislunar operations. Distributed computing and management will provide failure tolerance, robustness, and growth of capabilities while still allowing significant reuse of heritage software on heritage systems as well as reuse of common applications across a spacecraft to minimize new development, but this requires adherence to key standards and interfaces. The Gateway program has demonstrated significant progress towards these capabilities and has identified challenges other spacecraft developers should be aware of from the start.

Molly Anderson↗

Gateway Autonomy for Enabling Deep Space Exploration

The Gateway spacecraft is an important stepping-stone to exploration of the solar system, integrating commercial and international partners into a tightly coupled system, enabling cislunar activities, and implementing key technologies for missions to Mars. Autonomy is a capability area necessary to handle long communication outages where intervention from Earth is impossible, to prepare to operate with long communication delays that will be common in interplanetary travel, and to make spaceflight more affordable and accessible by reducing sustaining operations costs. The Gateway Concept of Operations states that one of Gateway’s goals is to “focus on infrastructure and systems that will allow autonomous operations aboard the Gateway with robotics, automated systems, advanced communications, and distributed computing.” Gateway’s Vehicle Systems Manager (VSM) and associated Autonomous Spacecraft Management Architecture (ASMA) are key products towards delivering autonomous capability. The primary functions of the control architecture are Mission Management and Timeline Execution, Resource Management, Fault Management, and Vehicle Control and Operation (VCO). In each of these areas, there is an initial level of capability to be delivered at launch, with plans to continue development and grow to greater capability. The initial deployment of VSM will focus on maintaining vehicle safety by focusing on full fault management capabilities and deploying only enough resource and timeline planning functionality to support that. The final deployment of VSM will add significant planning and control optimization functionality to support nominal operations for up to 21 days without ground support, even accommodating fault and failure conditions. While the VSM is the vehicle-level representation of autonomous reasoning, distributed automation is essential to provide the right scope and abstraction of information to process. Module and system support of automation and simplicity of interfaces are two important design paradigms that Gateway is focusing on to garner a systems approach to autonomy. Distribution of reasoning can increase complexity, so Gateway is also taking a strict hierarchical approach to information flow and decision making. VSM is not the only capability necessary to achieve an autonomous spacecraft. Robotics support for maintenance of the spacecraft will be essential to provide continued vehicle functionality even when crew is not present. Technical and programmatic challenges exist when implementing autonomous robotics operations. These challenges include sufficient network flexibility to support data transfer to the rest of the vehicle to coordinate module-to-module robotic walk-offs and finding the proper interfaces to allow sufficient dexterity. Communication system upgrades planned for Gateway include Delay Tolerant Networking to best utilize the complex network of relays that will be part of mature cislunar operations. Distributed computing and management will provide failure tolerance, robustness, and growth of capabilities while still allowing significant reuse of heritage software on heritage systems as well as reuse of common applications across a spacecraft to minimize new development, but this requires adherence to key standards and interfaces. The Gateway program has demonstrated significant progress towards these capabilities and has identified challenges other spacecraft developers should be aware of from the start.

Molly Anderson↗

Understanding Superionic Conductivity in Lithium and Sodium Salts of Weakly Coordinating Closo -Hexahalocarbaborate Anions

Solid-state ion conductors based on closo-polyborate anions combine high ionic conductivity with a rich array of tunable properties. Cation mobility in these systems is intimately related to the strength of the interaction with the neighboring anionic network and the energy for reorganizing the coordination polyhedra. In this paper, we explore such factors in solid electrolytes with two anions of the weakest coordinating ability, [HCB 11 H 5 Cl 6 ] – and [HCB 11 H 5 Br 6 ] – , and a total of 11 polymorphs are identified for their lithium and sodium salts. Our approach combines ab initio molecular dynamics, synchrotron X-ray powder diffraction, differential scanning calorimetry, and AC impedance measurements to investigate their structures, phase-transition behavior, anion orientational mobilities, and ionic conductivities. We find that M(HCB 11 H 5 X 6 ) (M = Li, Na, X = Cl, Br) compounds exhibit order–disorder polymorphic transitions between 203 and 305 °C and display Li and Na superionic conductivity in the disordered state. Through detailed analysis, we illustrate how cation disordering in these compounds originates from a competitive interplay among the lattice symmetry, the anion reorientational mobility, the geometric and electronic asymmetry of the anion, and the polarizability of the halogen atoms. These factors are compared to other closo-polyborate-based ion conductors to suggest guidelines for optimizing the cation–anion interaction for fast ion mobility. This study expands the known solid-state poly(carba)borate-based materials capable of liquid-like ionic conductivities, unravels the mechanisms responsible for fast ion transport, and provides insights into the development of practical superionic solid electrolytes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Center for Advanced Computational Technology

The Center for Advanced Computational Technology (ACT) was established to serve as a focal point for diverse research activities pertaining to application of advanced computational technology to future aerospace systems. These activities include the use of numerical simulations, artificial intelligence methods, multimedia and synthetic environments, and computational intelligence, in the modeling, analysis, sensitivity studies, optimization, design and operation of future aerospace systems. The Center is located at NASA Langley and is an integral part of the School of Engineering and Applied Science of the University of Virginia. The Center has four specific objectives: 1) conduct innovative research on applications of advanced computational technology to aerospace systems; 2) act as pathfinder by demonstrating to the research community what can be done (high-potential, high-risk research); 3) help in identifying future directions of research in support of the aeronautical and space missions of the twenty-first century; and 4) help in the rapid transfer of research results to industry and in broadening awareness among researchers and engineers of the state-of-the-art in applications of advanced computational technology to the analysis, design prototyping and operations of aerospace and other high-performance engineering systems. In addition to research, Center activities include helping in the planning and coordination of the activities of a multi-center team of NASA and JPL researchers who are developing an intelligent synthesis environment for future aerospace systems; organizing workshops and national symposia; as well as writing state-of-the-art monographs and NASA special publications on timely topics.

Noor, Ahmed K.↗

Evaluation of Intranasal Scopolamine for the Prevention of Wave Motion Induced Motion Sickness While Maintaining Performance on Operationally Relevant Tasks

Motion sickness represents one of the greatest clinical challenges impacting crew activities during and following g-transitions. Our overall goal is to characterize the effectiveness of motion sickness countermeasures during controlled laboratory experiments using capsule wave motion simulation and during field testing in operational environments. This laboratory study focused on prevention of motion sickness using intranasal scopolamine using a double-blinded repeated measures design in 30 subjects (19M, 11F). Intranasal scopolamine was provided by Defender Pharmaceuticals, Inc. (DPI-386 Nasal Gel, referred to as Inscop) self-administered by a nasal pump (Aptar Pharma) that delivers 0.4 mg dose (0.2 mg / nostril). During each session, subjects were exposed to complex wave motion on a six degree-of-freedom platform that included pitch, roll and heave at provocative stimulus frequencies (0.1-0.25 Hz) while seated in an illuminated cabin deprived of external visual cues. Motion sickness symptoms were compared across treatment and placebo control sessions counterbalanced across subjects and separated by at least one week. The time-to-motion sickness endpoint was based on severe malaise, defined as symptom score of ≥8 points using the Pensacola Diagnostic Index [1]. The bioavailability of scopolamine for each session was estimated from plasma concentrations obtained every 15 min[2]. Side effects during the treatment session were minimal, and performance was not impaired on a test battery including motion perception tracking, tablet-based eye-hand coordination and psychomotor vigilance testing. The plasma concentration remained near-peak levels throughout the 45 min motion sickness testing for most subjects. The percentile ranking on the Motion Sickness Susceptibility Questionnaire [MSSQ, 3]was moderately correlated with the motion sickness time-to-endpoint during the placebo control session (rho = –0.3, p=0.056). Seventeen subjects did not reach an endpoint during their placebo session and were eliminated from subsequent analysis. Another subject was excluded due to insufficient plasma concentration during the treatment session. For the remaining 12 subjects, the change in time-to-motion sickness endpoint between placebo and treatment sessions was moderately correlated with plasma concentration (rho =0.48, p = 0.056), improving on average 4.4 ± 18.4 min, mean ± std with Inscop versus placebo. Our results are consistent with previous findings that intranasal delivery of scopolamine can be effective at reducing motion sickness symptoms with minimal cognitive or sedative side effects. Future work is needed to optimize the delivery of Inscop for rescue (treatment) of symptoms following g-transitions as one of the key advantages of this formulation is self-administration in a suited environment. We will also explore how the combination of Inscop with non-pharmaceutical sensory aids, e.g., vibrotactile feedback of Earth vertical, may further mitigate motion sickness and improve task performance.

S J Wood↗

Numerical Modeling of a Vortex Stabilized Arcjet

Arcjet thrusters are being actively considered for use in Earth orbit maneuvering applications. Experimental studies are currently the chief means of determining an optimal thruster configuration. Earlier numerical studies have failed to include all of the effects found in typical arcjets including complex geometries, viscosity, and swirling flow. Arcjet geometries are large area ratio converging nozzles with centerbodies in the subsonic portion of the nozzle. The nozzle walls serve as the anode while the centerbody functions as the cathode. Viscous effects are important because the Reynolds number, based on the throat radius, is typically less than 1,000. Experimental studies have shown that a swirl or circumferential velocity component stabilizes a constricted arc. This dissertation describes the equations governing flow through a constricted arcjet thruster. An assumption that the flowfield is in local thermodynamic equilibrium leads to a single fluid plasma temperature model. An order of magnitude analysis reveals the governing fluid mechanics equations are uncoupled from the electromagnetic field equations. A numerical method is developed to solve the governing fluid mechanics equations, the Thin Layer Navier-Stokes equations. A coordinate transformation is employed in deriving the governing equations to simplify the application of boundary conditions in complex geometries. An axisymmetric formulation is employed to include the swirl velocity component as well as the axial and radial velocity components. The numerical method is an implicit finite-volume technique and allows for large time steps to reach a converged steady-state solution. The inviscid fluxes are flux-split, and Gauss-Seidel line relaxation is used to accelerate convergence. Converging-diverging nozzles with exit-to-throat area ratios up to 100:1 and annular nozzles were examined. Quantities examined included Mach number and static wall pressure distributions, and oblique shock structures. As the level of swirl and viscosity in the flowfield increased the mass flow rate and thrust decreased. The technique was used to predict the flow through a typical arcjet thruster geometry. Results indicate swirl and viscosity play an important role in the complex geometry of an arcjet.

Pawlas, Gary E.↗

Description of real-time Ada software implementation of a power system monitor for the Space Station Freedom PMAD DC testbed

The Ada language software development to perform the electrical system monitoring functions for the NASA Lewis Research Center's Power Management and Distribution (PMAD) DC testbed is described. The results of the effort to implement this monitor are presented. The PMAD DC testbed is a reduced-scale prototype of the electrical power system to be used in the Space Station Freedom. The power is controlled by smart switches known as power control components (or switchgear). The power control components are currently coordinated by five Compaq 382/20e computers connected through an 802.4 local area network. One of these computers is designated as the control node with the other four acting as subsidiary controllers. The subsidiary controllers are connected to the power control components with a Mil-Std-1553 network. An operator interface is supplied by adding a sixth computer. The power system monitor algorithm is comprised of several functions including: periodic data acquisition, data smoothing, system performance analysis, and status reporting. Data is collected from the switchgear sensors every 100 milliseconds, then passed through a 2 Hz digital filter. System performance analysis includes power interruption and overcurrent detection. The reporting mechanism notifies an operator of any abnormalities in the system. Once per second, the system monitor provides data to the control node for further processing, such as state estimation. The system monitor required a hardware time interrupt to activate the data acquisition function. The execution time of the code was optimized using an assembly language routine. The routine allows direct vectoring of the processor to Ada language procedures that perform periodic control activities. A summary of the advantages and side effects of this technique are discussed.

Ludwig, Kimberly↗

Convex Relaxations of Maximal Load Delivery for Multi-Contingency Analysis of Joint Electric Power and Natural Gas Transmission Networks

Recent increases in gas-fired power generation have engendered increased interdependencies between natural gas and power transmission systems. These interdependencies have amplified existing vulnerabilities in gas and power grids, where disruptions can require the curtailment of load in one or both systems. Although typically operated independently, coordination of these systems during severe disruptions can allow for targeted delivery to lifeline services, including gas delivery for residential heating and power delivery for critical facilities. To address the challenge of estimating maximum joint network capacities under such disruptions, we consider the task of determining feasible steady-state operating points for severely damaged systems while ensuring the maximal delivery of gas and power loads simultaneously, represented mathematically as the nonconvex joint Maximal Load Delivery (MLD) problem. To increase its tractability, we present a mixed-integer convex relaxation of the MLD problem. Then, to demonstrate the relaxation’s effectiveness in determining bounds on network capacities, exact and relaxed MLD formulations are compared across various multi-contingency scenarios on nine joint networks ranging in size from 25 to 1191 nodes. The relaxation-based methodology is observed to accurately and efficiently estimate the impacts of severe joint network disruptions, often converging to the relaxed MLD problem’s globally optimal solution within ten seconds.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Optimal Planning and Problem-Solving

CTAEMS MDP Optimal Planner is a problem-solving software designed to command a single spacecraft/rover, or a team of spacecraft/rovers, to perform the best action possible at all times according to an abstract model of the spacecraft/rover and its environment. It also may be useful in solving logistical problems encountered in commercial applications such as shipping and manufacturing. The planner reasons around uncertainty according to specified probabilities of outcomes using a plan hierarchy to avoid exploring certain kinds of suboptimal actions. Also, planned actions are calculated as the state-action space is expanded, rather than afterward, to reduce by an order of magnitude the processing time and memory used. The software solves planning problems with actions that can execute concurrently, that have uncertain duration and quality, and that have functional dependencies on others that affect quality. These problems are modeled in a hierarchical planning language called C_TAEMS, a derivative of the TAEMS language for specifying domains for the DARPA Coordinators program. In realistic environments, actions often have uncertain outcomes and can have complex relationships with other tasks. The planner approaches problems by considering all possible actions that may be taken from any state reachable from a given, initial state, and from within the constraints of a given task hierarchy that specifies what tasks may be performed by which team member.

Clemet, Bradley↗

Local Estimators for Spacecraft Formation Flying

A formation estimation architecture for formation flying builds upon the local information exchange among multiple local estimators. Spacecraft formation flying involves the coordination of states among multiple spacecraft through relative sensing, inter-spacecraft communication, and control. Most existing formation flying estimation algorithms can only be supported via highly centralized, all-to-all, static relative sensing. New algorithms are needed that are scalable, modular, and robust to variations in the topology and link characteristics of the formation exchange network. These distributed algorithms should rely on a local information-exchange network, relaxing the assumptions on existing algorithms. In this research, it was shown that only local observability is required to design a formation estimator and control law. The approach relies on breaking up the overall information-exchange network into sequence of local subnetworks, and invoking an agreement-type filter to reach consensus among local estimators within each local network. State estimates were obtained by a set of local measurements that were passed through a set of communicating Kalman filters to reach an overall state estimation for the formation. An optimization approach was also presented by means of which diffused estimates over the network can be incorporated in the local estimates obtained by each estimator via local measurements. This approach compares favorably with that obtained by a centralized Kalman filter, which requires complete knowledge of the raw measurement available to each estimator.

Fathpour, Nanaz↗

Finite orbit width effects in large aspect ratio stellarators

New orbit-averaged equations for low collisionality neoclassical fluxes in large aspect ratio stellarators with mirror ratios close to unity are derived. The equations retain finite orbit width effects by employing the second adiabatic invariant $J$ as a velocity-space coordinate and they have been implemented in the orbit-averaged neoclassical code KNOSOS (Velasco et al. , J. Comput. Phys. , vol. 418, 2020, 109512; Velasco et al. , Nucl. Fusion , vol. 61, 2021, 116013). The equations are used to study the $1/\nu$ regime and the lower collisionality regimes. For generic large aspect ratio stellarators with mirror ratios close to unity, as the collision frequency decreases, the $1/\nu$ regime transitions directly into the $\nu$ regime, without passing through a $\sqrt {\nu }$ regime. An explicit formula for the neoclassical fluxes in the $\nu$ regime is obtained. The formula includes the effect of particles that transition between different types of wells. While these transitions produce stochastic scattering independent of the value of the collision frequency in velocity space, the diffusion in real space remains proportional to the collision frequency. The $\sqrt {\nu }$ regime is only recovered in large aspect ratio stellarators close to omnigeneity: large aspect ratio stellarators with large mirror ratios and optimized large aspect ratio stellarators with mirror ratios close to unity. Neoclassical transport in large aspect ratio stellarators with large mirror ratios can be calculated with the orbit-averaged equations derived by Calvo et al. ( Plasma Phys. Control. Fusion , vol. 59, 2017, 055014). In these stellarators, the $\sqrt {\nu }$ regime exists in the collisionality interval $(a/R) \ln (R/a) \ll \nu _{ii} R a/\rho _i v_{ti} \ll R/a$ . In optimized large aspect ratio stellarators with mirror ratios close to unity, the $\sqrt {\nu }$ regime occurs in an interval of collisionality that depends on the deviation from omnigeneity $\delta$ : $\delta ^{2} |\ln \delta | \ll \nu _{ii} R a/\rho _i v_{ti} \ll 1$ . Here, $\nu _{ii}$ is the ion–ion collision frequency, $\rho _i$ and $v_{ti}$ are the ion gyroradius and thermal speed, and $a$ and $R$ are the minor and major radii.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Different Perspectives on Asthenia in Astronauts and Cosmonauts: International Research Literature

The Behavioral Health and Performance (BHP) Element is one of the six elements within the NASA Human Research Program (HRP) and is responsible for managing four risks: a) The Risk of Performance Decrements due to inadequate Cooperation, Coordination, Communication and Psychological Adaptation within a Team (Team), b) the Risk of Performance Errors due to Sleep Loss, Circadian De-synchronization, Fatigue and Work Overload (Sleep), c) Risk of Behavioral Conditions (BMed), and d) the Risk of Psychiatric Disorders (BMed). The aim of this report is to address some of the recommendations made by the recent NASA HRP Standing Review Panel for the Behavioral Medicine Risk of Psychiatric Disorders. Such recommendations included: a) the inclusion of important national and international literature in English and non-English language materials; including journals, books, magazines, conference reports and b) an extensive literature review of certain types of psychological states to predict, detect, and assess adverse mental states that may negatively affect the psychological well being of the astronauts, specifically asthenia. This report was a collaborative international work effort focused on the evaluation and determination of the importance of continuing research on asthenia as a possible psychological problem that might affect the optimal psychological functioning among crewmembers during long-duration space flight missions. Russian medical personnel (flight surgeons and psychologist) have observed symptoms of asthenia (weakness, increased fatigue, irritability, and attention and memory disorders) in cosmonauts after four months in space (Myasnikov& Zamaleddinov1996; Grigorieve, 1996 ) and believe that asthenia is one of the greater risks that will affect crews? optimal psychological functioning.

Sandoval, Luis↗

Navigating Transition-Metal Chemical Space: Artificial Intelligence for First-Principles Design

Conspectus The variability of chemical bonding in open-shell transition-metal complexes not only motivates their study as functional materials and catalysts but also challenges conventional computational modeling tools. Here, tailoring ligand chemistry can alter preferred spin or oxidation states as well as electronic structure properties and reactivity, creating vast regions of chemical space to explore when designing new materials atom by atom. Although first-principles density functional theory (DFT) remains the workhorse of computational chemistry in mechanism deduction and property prediction, it is of limited use here. DFT is both far too computationally costly for widespread exploration of transition-metal chemical space and also prone to inaccuracies that limit its predictive performance for localized d electrons in transition-metal complexes. These challenges starkly contrast with the well-trodden regions of small-organic-molecule chemical space, where the analytical forms of molecular mechanics force fields and semiempirical theories have for decades accelerated the discovery of new molecules, accurate DFT functional performance has been demonstrated, and gold-standard methods from correlated wavefunction theory can predict experimental results to chemical accuracy. The combined promise of transition-metal chemical space exploration and lack of established tools has mandated a distinct approach. In this Account, we outline the path we charted in exploration of transition-metal chemical space starting from the first machine learning (ML) models (i.e., artificial neural network and kernel ridge regression) and representations for the prediction of open-shell transition-metal complex properties. The distinct importance of the immediate coordination environment of the metal center as well as the lack of low-level methods to accurately predict structural properties in this coordination environment first motivated and then benefited from these ML models and representations. Once developed, the recipe for prediction of geometric, spin state, and redox potential properties was straightforwardly extended to a diverse range of other properties, including in catalysis, computational “feasibility”, and the gas separation properties of periodic metal–organic frameworks. Interpretation of selected features most important for model prediction revealed new ways to encapsulate design rules and confirmed that models were robustly mapping essential structure–property relationships. Encountering the special challenge of ensuring that good model performance could generalize to new discovery targets motivated investigation of how to best carry out model uncertainty quantification. Distance-based approaches, whether in model latent space or in carefully engineered feature space, provided intuitive measures of the domain of applicability. With all of these pieces together, ML can be harnessed as an engine to tackle the large-scale exploration of transition-metal chemical space needed to satisfy multiple objectives using efficient global optimization methods. In practical terms, bringing these artificial intelligence tools to bear on the problems of transition-metal chemical space exploration has resulted in ML-model assessments of large, multimillion compound spaces in minutes and validated new design leads in weeks instead of decades.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Enabling Scalable and Extensible Memory-mapped Datastores in Userspace

Exascale workloads are expected to incorporate data-intensive processing in close coordination with traditional physics simulations. These emerging scientific, data-analytics and machine learning applications need to access a wide variety of datastores in flat files and structured databases. Programmer productivity is greatly enhanced by mapping datastores into the application process's virtual memory space to provide a unified “in-memory” interface. Currently, memory mapping is provided by system software primarily designed for generality and reliability. However, scalability at high concurrency is a formidable challenge on exascale systems. Also, there is a need for extensibility to support new datastores potentially requiring HPC data transfer services. In this article, we present UMap , a scalable and extensible userspace service for memory-mapping datastores. Furthermore, through decoupled queue management, concurrency aware adaptation, and dynamic load balancing, UMap enables application performance to scale even at high concurrency. We evaluate UMap in data-intensive applications, including sorting, graph traversal, database operations, and metagenomic analytics. Our results show that UMap as a userspace service outperforms an optimized kernel-based service across a wide range of intra-node concurrency by 1.22-1.9 × . We performed two case studies to demonstrate UMap 's extensibility. First, a new datastore residing in remote memory is incorporated into UMap as an application-specific plugin. Second, we present a persistent memory allocator Metall built atop UMap for unified storage/memory.

97 MATHEMATICS AND COMPUTING↗

A programming environment for distributed complex computing. An overview of the Framework for Interdisciplinary Design Optimization (FIDO) project. NASA Langley TOPS exhibit H120b

The Framework for Interdisciplinary Design Optimization (FIDO) is a general programming environment for automating the distribution of complex computing tasks over a networked system of heterogeneous computers. For example, instead of manually passing a complex design problem between its diverse specialty disciplines, the FIDO system provides for automatic interactions between the discipline tasks and facilitates their communications. The FIDO system networks all the computers involved into a distributed heterogeneous computing system, so they have access to centralized data and can work on their parts of the total computation simultaneously in parallel whenever possible. Thus, each computational task can be done by the most appropriate computer. Results can be viewed as they are produced and variables changed manually for steering the process. The software is modular in order to ease migration to new problems: different codes can be substituted for each of the current code modules with little or no effect on the others. The potential for commercial use of FIDO rests in the capability it provides for automatically coordinating diverse computations on a networked system of workstations and computers. For example, FIDO could provide the coordination required for the design of vehicles or electronics or for modeling complex systems.

Townsend, James C.↗