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At least 1,477 records · Page 82

Performance of Coupled Physics Solvers for Multidisciplinary Hypersonic Flow Simulations on Several Classes of Computer Architectures

The application of hypersonic flow simulation tools to realistic flight scenarios will require the coupling of multiple physical effects to the baseline fluid dynamics. Such multiphysics effects can include the aerooelastic response of the airframe or engine components, dynamic transport of atmospheric particles, the deformation of solid-fluid interfaces that can ablate, pyrolyze, or erode, as well as a host of other processes, all of which are governed by unique sets of physical equations and models. Coupling multiple (and potentially disparate) physics solvers to a robust compressible flow solver poses additional challenges related to the stability, performance and scalability of the combined solver. The choices made during the software design process can therefore lead to a variation in simulation efficiency across different computer architectures. In this paper, we will consider two representative multiphysics hypersonic flow scenarios: the interaction of solid particulates with the flow field created by a hypersonic lifting body and the aerooelastic deformation of a model airframe under high-Mach-number flow conditions. For these simulations we explore the behavior of several hypersonic simulation tools, including Kestrel, FUN3D, US3D, and JENRE multiphysics framework, on several high performance computing systems containing various CPU and GPU architectures.

architecture↗

Development of a Comprehensive Physics-Based Model for Study of NASA Gateway Lunar Dust Contamination

NASA is committed to landing the first woman and first person of color on the Moon by 2025 to begin a sustaining presence. A major component of this mission is NASA’s orbiting lunar outpost, Gateway, that will be subjected to the harsh environment of space during its 7-day orbit around the Moon. One aspect of this environment that is not well quantified is microscopic lunar regolith particles, or simply, lunar dust. As Apollo 17 Mission Commander Eugene Cernan said, “I think dust is probably one of our greatest inhibitors to a nominal operation on the moon. I think we can overcome other physiological or physical or mechanical problems except dust” [1]. These dust particles, most of which are smaller than the width of two human hairs and of highly irregular shape, are composed mainly of dielectric materials. Such characteristics can allow the dust particles to collect electric charge from the surrounding environment, resulting in electrostatic interactions between the dust, electromagnetic fields, and electrically charged surfaces [2-3]. Due to the nature of these fields, dust can collect on and contaminate charged surfaces. Lunar dust introduced into the Gateway environment by a lunar ascent vehicle element returning from the surface of the Moon presents risks to Gateway hardware such as radiators, solar arrays, antennae, and docking mechanisms. To quantify this risk and inform NASA, International Partner, and Commercial Provider stakeholders, Booz Allen, in partnership with NASA, is developing a toolset to model the interaction of charged lunar dust particles with the cis-lunar and deep-space environments. This includes a comprehensive physics model of the space plasma and solar radiation environment and electromagnetic interaction of spacecraft and lunar dust. Spacecraft charging and plasma environment are solved using the open-source code from The French Aerospace Lab (ONERA) and the European Space Agency (ESA), known as Spacecraft Plasma Interaction Software (SPIS) [4]. The physics of particle charging and motion is handled by a time-dependent implementation of Orbital-Motion-Limited (OML) theory which accounts for plasma flows and positive potential grains [5-7], using Siemens STAR-CCM+ as the framework. Model validation includes lab experiments by NASA experts and academia, as well as future on-orbit dust detecting payloads on the exterior of Gateway and Commercial Lunar Payload Services (CLPS) missions to the lunar surface [7-9]. The results and analyses will inform Gateway Program system owners at risk for lunar dust contamination.

Complex Plasma↗

A Preliminary Assessment of Physical Demand during Simulated Lunar Surface Extravehicular Activities

Returning to the moon requires many advances in current space technology. One major aspect of this development is a new exploration spacesuit (xEMU). Taking lessons learned from Apollo era suitsand the Extravehicular Mobility Unit (EMU) used on the International Space Station (ISS), xEMU will have increased mobility, dust mitigation, headspace, glove fit, and life support capabilities. Artemis astronauts in xEMU will complete a far more rigorous Extravehicular Activity (EVA) schedule than Apolloand ISS. Notably, metabolic rates during Apollo lunar EVA tasks were observed to be up to 50% lower than similar tasks performed in a ground analog environment under simulated partial gravity with newer suits. Therefore, understanding the physical demands of lunar surface exploration operations is criticalto ensuring best outcomes operating within the constraints of xEMU and planning for exploration EVA activities. This study utilized the Active Response Gravity Offload System (ARGOS) to simulate the lunar environment and continuously offload subjects to lunar gravity. Two male subjects completed two days of EVAs wearing the pressurized Mark III spacesuit, completing suit fit and mobility checks, as well as simulated lander operations, cable routing, crew rescue, geology, payload relocation, and traverse tasks in an end-to-end EVA (E2E) task block and standalone (SA) task blocks. We recorded continuous values of metabolic rate (MR) and heart rate (HR) to assess physical demand. During the E2E task block, subjects did not rest between tasks to simulate continuous effort from task to task, as in real EVAs. In comparison, subjects had a 5-minute break after each SA task block to allow for the metabolic rate and heart rate to return to baseline.MR values were categorized as low (≤ 700 BTU/hr), medium (700-1000 BTU/HR), and high (≥ 1000 BTU/hr), while HR values were categorized as low (≤150) and high (>150). During the 16 tasks in the E2E block, subjects averaged low MR in 6% of tasks, medium MR in 47% of tasks, and high MR in 47% of tasks. While MR was consistent between subjects, Subject 1 averaged low HR for 100% of these tasks, while Subject 2 averaged low HR in 44% of tasks. During the 23 tasks in the SA task blocks, subjects averaged low MR in 26% of tasks, medium MR in 52% of tasks, and high MR in 22% of tasks. Again, HR was different between subjects, with subject 1 averaging low HR in 100% of these tasks while subject 2 averaged low HR in 70%. Across all tasks in this study, subjects reached maximum MR and HR values during a 500m traverse at 30% grade in the E2E block (subject 1: 1747 BTU/hr, 150 BPM; subject 2: 1656 BTU/hr, 177 BPM).Understanding the physical demand to complete exploration EVA tasks will be instrumental to the future success of exploration spacesuit designs and missions. Further work in this study will be needed to characterize MR during exploration EVA tasks, including expanding the subject pool and testing new suit designs.

Taylor E Schlotman↗

A Preliminary Assessment of Physical Demand During Simulated Lunar Surface Extravehicular Activities

Future Artemis missions will require more advanced spacesuits to support exploration and science activities on the Lunar surface. Preparing for these missions requires an understanding of the physical and cognitive demand of performing common surface extravehicular activity (EVA) tasks in a suited partial-gravity environment. This study aims to characterize physical demand during exploration EVA tasks in the Artificial Gravity Offload System (ARGOS) as a function of the task and operational environment itself. Two subjects completed two days of EVA simulations at ARGOS in the Mark III spacesuit offloaded to Lunar gravity (1/6G). Metabolic rate (MR) and heart rate (HR) were continuously recorded while subjects completed an end-to-end EVA as well as standalone tasks. Understanding the physical demand to complete exploration EVA tasks will be instrumental to the future success of exploration spacesuit designs and missions. Further work in this study will be needed to characterize MR during exploration EVA tasks, including expanding the subject pool and testing new suit designs.

Taylor E Schlotman↗

INFLUENCE OF ACTN3 GENE ON MUSCLE HEALTH AND PHYSICAL FITNESS TO INFORM FUTURE INTERVENTIONS IN SPACEFLIGHT MISSIONS

INTRODUCTION: Exposure to reduced gravity environments leads to diminished muscle size, strength, and endurance. Preservation of physical fitness is critical for mission essential tasks such as extravehicular activities or adaptation to changes in gravity loads. Current countermeasures to maintain ISS astronauts’ muscle mass and fitness include dedicated time for a combination of cardiovascular exercise and resistance training. Countermeasure effectiveness is monitored through VO2 max and isometric mid-thigh pulls. It is important to understand both environmental and genetic contributors to astronaut physical fitness. Multiple genes, including ACTN3, are known to correlate with exercise phenotypes and have the potential to help personalize countermeasures based on an astronaut’s genotypic makeup. TOPIC: The ACTN3 gene encodes a protein expressed only in fast-twitch muscles and correlates with sprint and power phenotypes. A common polymorphism in ACTN3 gene is R577X (rs1815739), produced by a C−to−T base substitution resulting in a nonsense mutation from arginine (R) to a premature stop codon (X) present in approximately 18% of the population. This polymorphism causes an absence of α−actinin−3 in type II muscle fibers but does not lead to a disease phenotype. The RR genotype is associated with elite athletes, especially in sprint and power sports. The XX genotype is believed to be more common in endurance athletes. The ACTN3 gene also has potential associations with training adaptation, post-exercise recovery, and exercise-associated injuries. APPLICATION: Understanding how ACTN3 and other genetic determinates of fitness phenotypes affect astronaut physical performance can inform personalized exercise and recovery prescriptions. For example, individuals with the RR or RX genotype may respond better to high-load and low repetition exercise, while XX may benefit from high repetition with low weight exercise. Since the wild-type protein may confer more resistance to muscle damage, those individuals with the RR or RX genotype may benefit from high intensity interval training for improved VO2 max, whereas those with an XX genotype may benefit from low intensity, high volume endurance activity. Additionally, omics data related to health and performance could be used as biomarkers to monitor astronaut fitness and the effectiveness of training regimens during a mission. Learning objectives: • Learn about the phenotypic effects on muscle function and fitness secondary to R577X mutation in the ACTN3 gene • Learn how mutations in the ACTN3 gene may inform future countermeasures for future spaceflight missions

Lynn K Stanwyck↗

Role of Cyber-Physical Testing in Developing Resilient Extraterrestrial Habitats

Extraterrestrial long-term habitat systems (henceforth referred to as habitat systems) require groundbreaking technological advances to overcome the extreme demands introduced by isolation and challenging environments. A habitat system must operate as intended under continuous disruptive conditions. Designing for the demands that challenging environments will place on habitat systems (e.g., wild temperature fluctuations, galactic cosmic rays, destructive dust, meteoroid impacts, vibrations, and solar particle events) represents one of the greatest challenges in this endeavor. This engineering problem necessitates that we design and manage habitat systems to be resilient. System resilience requires a comprehensive approach that accounts for disruptions through the design process and adapts to them in operation. As the habitat system evolves—growing in physical size, complexity, population, and connectivity—and diversifies in operations, it must continue to be safe and resilient. In this endeavor, we should take advantage of lessons learned in developing civil infrastructure responsive to catastrophic natural hazards, autonomous robotics platforms, smart buildings, cyber-physical testing, complex systems, and diagnostics and prognostics for intelligent health management. This study highlights the importance of system resilience and cyber-physical testing to address the grand challenge of developing habitat systems.

Public health and safety↗

Broader Impacts and Outreach Videos on Ocean Physics and Biogeochemistry

This is just a preliminary NF1676 in advance of filming for a project....A convergent team of experts in biology, chemistry, physics, engineering, mathematics, and computational modeling examine how dynamic and coupled phytoplankton-pathogen-particle-predator linkages coalesce to explain the observed high spatial variability in the efficiency of the export of particulate organic carbon (POC) to the deep ocean. They elucidate and quantify the linkages between viruses and ballast minerals to increase understanding of carbon cycling in the oceanic biological carbon pump and the impact of viruses within it. By providing knowledge than can be used to improve the parameterization of carbon export in Earth system models, the project will help reduce uncertainty in regional marine biogeochemical projections, potentially improving marine ecosystem and fisheries management on timescales from seasons to decades. The project includes activities that provide teaching resources and hands-on training to educators within a ‘Tools of Science’ program that provides a simple and succinct way to communicate the process of scientific research to students in a way that is useful to teachers. The project couples laboratory-based experiments on model host-virus-grazer systems with extensive field based observational and manipulative studies on natural populations of diatoms and coccolithophores, the two phytoplankton groups that account for most of the estimated particulate organic matter flux to the deep ocean. Experiments and measurements integrate diagnostic biological and chemical controls on infection and particle coagulation theory with microscale physics and grazing to quantify links to each hypothesized export mechanism under field-relevant turbulent conditions. Cutting-edge engineering and analytical tools are used to diagnose and track infection dynamics while characterizing and quantifying particle aggregation and disaggregation, mineral dissolution, sinking dynamics, grazing rates, and fecal pellet production at unprecedented resolution and under well-defined, microscale physical regimes. Field campaigns elucidate the relative efficiency of hypothesized mechanisms in stimulating POC export in natural blooms, while providing bulk and size-resolved estimates of POC flux.

Daniel B Whitt↗

Line Emission Mapper Probing Physics of Cosmic Ecosystems

The Line Emission Mapper (LEM) is an X-ray Probe for the 2030s that will answer the outstanding questions of the Universe’s structure formation. It will also provide transformative new observing capabilities for every area of astrophysics, and to heliophysics and planetary physics as well. LEM’s main goal is a comprehensive look at the physics of galaxy formation, including stellar and black-hole feedback and flows of baryonic matter into and out of galaxies. These processes are best studied in X-rays; as emphasized by the 2020 Decadal Survey, emission-line mapping is the pressing need in this area. LEM will use a large microcalorimeter array/IFU (that builds on Athena XIFU technology developments), covering a 30 × 300 field with 1000 angular resolution, to map the soft Xray line emission from objects that constitute galactic ecosystems. These include supernova remnants, star-forming regions, superbubbles, galactic outflows (such as the Fermi/eROSITA bubbles in the Milky Way and their analogs in other galaxies), the Circumgalactic Medium in the Milky Way and other galaxies, and the Intergalactic Medium at the outskirts and beyond the confines of galaxies and clusters. LEM’s 1–2 eV spectral resolution in the 0.2–2 keV band will make it possible to disentangle the faintest emission lines in those objects from the bright Milky Way foreground, providing groundbreaking measurements of the physics of these plasmas, from temperatures, densities, chemical composition to gas dynamics. While the mission is optimized to provide critical observations that will push our understanding of galaxy formation, LEM will provide transformative capability for all classes of astrophysical objects, from the Earth’s magnetosphere, planets and comets to the interstellar medium and X-ray binaries in nearby galaxies, AGN, and cooling gas in galaxy clusters. In addition to pointed observations, LEM will perform a shallow all-sky survey that will dramatically expand the discovery space.

Ralph Kraft↗

Parametric Mechanism Design Through Numerical Optimization and Physics Simulation

Design-Build-Test approaches for developing spaceflight hardware are prohibitively time and cost intensive and often lead to suboptimal mechanism designs. Approaches that couple machine learning and high-fidelity physics simulation could eliminate the need for hardware prototyping and dramatically accelerate the engineering design cycle, ultimately reducing cost. This work presents a modular NASA-developed toolchain to optimize hardware mechanisms in a virtual environment using numerical optimization and multi-body physics simulation. The toolchain enables multi-objective optimization, generates parametric CAD files that can be further post-processed by an end user, and can be expanded to optimize full systems and non-mechanical parameters such as feedback control variables. We demonstrate the toolchain through an independently verifiable design problem that optimizes wheel radius to achieve a desired linear velocity in a rigid-body physics environment when the wheel rotates at a constant angular speed, and then post-process the parametric CAD file of the optimal design generated by the tool before ultimately manufacturing it via 3D printing. We end with a discussion of how the toolchain can incorporate other analysis tools, including finite element analysis, computational fluid dynamics, and granular media simulations.

Optimization↗

Investigating the Physical Modification of the Bennu Sample During Entry, Descent, and Landing

On September 24, 2023, the OSIRIS-REx Sample Return Capsule (SRC) entered Earth’s atmosphere and landed in the Utah Test and Training Range (UTTR). Preliminary examination of the returned Bennu sample has confirmed that OSIRIS-REx sample mass exceeds the mission requirement of 60 g of material. The sample consists of particles that range from a few centimeters to microscopic fines. During the SRC’s entry, descent, and landing (EDL) sequence, it may have experienced (i) peak decelerations of 10s of g (ii) tumbling, and (iii) touchdown at approximately 10 m/s, which could have induced physical modification of the sample. In addition, the act of sampling may have altered or biased the physical properties of the collected materials. Here, we investigate the likelihood and extent of physical modification of the sample between collection and return using observations and modeling. This work addresses the mission’s hypothesis 12, which concerns, in part, the modification of the sample during collection and Earth entry.

asteroid↗

Icing Physics Studies Using the 3D SIDRM Test Article: Ice Crystal Icing Analysis

In-flight icing is an important safety issue and is a factor that affects aircraft design and performance. Newer regulations are driving a need for improvements in airframe and engine icing simulation capability. Experimental data is required for the development of icing physics models and simulation validation. This paper presents the analysis of the ice crystal icing data subset from tests conducted in 2022 at the NASA Icing Research Tunnel that studied both supercooled liquid and ice-crystal icing. The test article that was utilized replicated 3D geometrical features of an inter-compressor duct and strut region of a turbofan engine. The surfaces of the Simulated Inter-compressor Duct Research Model (SIDRM) can be heated to simulate the warm surfaces of the turbofan inter-compressor duct. The test article is instrumented with pressure taps, heaters, heat flux gauges, and thermocouples, while a 3D laser scanner, cameras, and a weighing scale to measure ice mass were utilized to characterize the icing behavior. The aim of these tests was to generate ice accretions on the SIDRM test article under well-characterized icing conditions. To that end, ice crystal cloud characterization tests were conducted that provided cloud property values at the test section. The ice crystal accretion tests investigated how different test condition parameters impacted ice accretion size, location, and characteristics (such as physical attributes). A key finding was that a sufficiently high surface heat flux at the leading edge can provide a continuous supply of liquid melt to critical accretion zones downstream, resulting in elevated ice mass accretions. Another key finding was that warmer heater settings in critical accretion zones can suppress ice accretion. These findings are consistent with icing behavior observed in full-scale engine icing tests conducted previously at the NASA Glenn Research Center. Test runs investigating the contribution of liquid melt generated at the leading edge found that the melt can be transported downstream to critical accretion regions in two forms, via runback and splash. The form of melt supplied downstream affected accretion behavior and features. Sharkteeth-shaped ice accretions were generated at certain test conditions, a physical attribute that has been observed in full-scale engine icing tests. The ice accretion data will be used to develop and validate 3D computational engine icing tools, such as GlennICE, that predictively assesses the onset and growth of ice. One of the goals of the sponsoring NASA project is to develop simulation models and tools that can assist in the design and certification of engines for flight in icing conditions in a cost‑effective way.

ice crystal icing↗

Utilization of Streamtubes to Analyze the Physical Interaction of a Dispersed Cloud with the CRM65 Hybrid Midspan Model

Recently there have been numerous efforts to identify the relevant icing physics related to the formation of complex three dimensional features, sometimes referred to as ’scallops’, on swept wings. However, much of the physics is still not well understood. This paper computationally investigates the interaction of the icing cloud with the 65 percent Common Research Model (CRM65). Both the interaction with an uniced model, and the interaction with a representative simulated three dimensional ice accretion are analyzed. Preliminary results suggest that the liquid water content increases near the aerodynamic body. For small droplets on the uniced geometry, the particle velocity vector becomes nearly parallel with the aerodynamic model resulting in a low value of collection efficiency. When a three dimensional feature with a length scale much smaller than the leading edge of the airfoil is introduced into the flow, the impingement of small particles can become significantly more perpendicular to the particle velocity vector in the region of these features. Since the liquid water content near the body has increased due to the interaction with the larger scale features of the aerodynamic model, i.e. the leading edge of the swept wing, extremely high collection efficiency is observed. These results suggest that three dimensional features are likely a significant physical driver that should be modeled in some capacity when simulating the impingement of a cloud on an aerodynamic model.

Icing↗

Icing Physics Studies Using the 3D SIDRM Test Article: Ice Crystal Icing Analysis

In-flight icing is an important safety issue and is a factor that affects aircraft design and performance. Newer regulations are driving a need for improvements in airframe and engine icing simulation capability. Experimental data is required for the development of icing physics models and simulation validation. This paper presents the analysis of the ice crystal icing data subset from tests conducted in 2022 at the NASA Icing Research Tunnel that studied both supercooled liquid and ice-crystal icing. The test article that was utilized replicated 3D geometrical features of an inter-compressor duct and strut region of a turbofan engine. The surfaces of the Simulated Inter-compressor Duct Research Model (SIDRM) can be heated to simulate the warm surfaces of the turbofan inter-compressor duct. The test article is instrumented with pressure taps, heaters, heat flux gauges, and thermocouples, while a 3D laser scanner, cameras, and a weighing scale to measure ice mass were utilized to characterize the icing behavior. The aim of these tests was to generate ice accretions on the SIDRM test article under well-characterized icing conditions. To that end, ice crystal cloud characterization tests were conducted that provided cloud property values at the test section. The ice crystal accretion tests investigated how different test condition parameters impacted ice accretion size, location, and characteristics (such as physical attributes). A key finding was that a sufficiently high surface heat flux at the leading edge can provide a continuous supply of liquid melt to critical accretion zones downstream, resulting in elevated ice mass accretions. Another key finding was that warmer heater settings in critical accretion zones can suppress ice accretion. These findings are consistent with icing behavior observed in full-scale engine icing tests conducted previously at the NASA Glenn Research Center. Test runs investigating the contribution of liquid melt generated at the leading edge found that the melt can be transported downstream to critical accretion regions in two forms, via runback and splash. The form of melt supplied downstream affected accretion behavior and features. Sharkteeth-shaped ice accretions were generated at certain test conditions, a physical attribute that has been observed in full-scale engine icing tests. The ice accretion data will be used to develop and validate 3D computational engine icing tools, such as GlennICE, that predictively assesses the onset and growth of ice. One of the goals of the sponsoring NASA project is to develop simulation models and tools that can assist in the design and certification of engines for flight in icing conditions in a cost‑effective way.

ice crystal icing↗

Utilization of Streamtubes to Analyze the Physical Interaction of a Dispersed Cloud with the CRM65 Hybrid Midspan Model

Recently there have been numerous efforts to identify the relevant icing physics related to the formation of complex three dimensional features, sometimes referred to as ’scallops’, on swept wings. However, much of the physics is still not well understood. This paper computationally investigates the interaction of the icing cloud with the 65 percent Common Research Model (CRM65). Both the interaction with an uniced model, and the interaction with a representative simulated three dimensional ice accretion are analyzed. Preliminary results suggest that the liquid water content increases near the aerodynamic body. For small droplets on the uniced geometry, the particle velocity vector becomes nearly parallel with the aerodynamic model resulting in a low value of collection efficiency. When a three dimensional feature with a length scale much smaller than the leading edge of the airfoil is introduced into the flow, the impingement of small particles can become significantly more perpendicular to the particle velocity vector in the region of these features. Since the liquid water content near the body has increased due to the interaction with the larger scale features of the aerodynamic model, i.e. the leading edge of the swept wing, extremely high collection efficiency is observed. These results suggest that three dimensional features are likely a significant physical driver that should be modeled in some capacity when simulating the impingement of a cloud on an aerodynamic model.

Icing↗

Physical Parameters of Space Mission Asteroid Targets

Ground-based characterization of asteroids that are planned or potential targets of space missions provides important data on their physical parameters and properties. Knowledge of the properties of mission targets is important especially during mission preparation and planning, as it serves to select best or suitable targets for specific purpose of a given mission, to prepare mission plans, to constrain possible mission scenarios, and to design mission experiments. Such characterization efforts may be particularly critical for flyby missions that take only limited data during the high-speed flybys of their target asteroids, but they also provide very crucial data for targets of rendezvous missions. Moreover, long-term observations taken from Earth also allows the modelling of, or constraining, processes acting on the asteroids over extended time scales. Over the past years and decades we have obtained rich data on physical parameters of 82 asteroids that are planned or potential targets of space missions. Our primary observing technique is time-resolved (lightcurve) photometry, but we use also data obtained with other techniques, such as spectroscopy, thermal or radar observations. 15 of the 82 characterized asteroids are planned or possible targets of several space missions that are in flight or preparation, such as ESA’s Hera, RAMSES and PRIAMOS, NASA’s OSIRIS-APEX, JAXA’s Hayabusa2#, DESTINY+ and Next Generation Sample Return (NGSR), the Emirates Mission to Asteroids (EMA), and Karman+’s High Frontier, but we have also characterized 67 asteroids that are potential targets of space missions for their low delta-V’s and were announced as being “of interest to NASA” in the Small-Bodies-Observations- NASA mailing list or listed on the NHATS page of “Accessible NEAs”. The sample of asteroid targets span 3 orders of magnitude in size, with absolute magnitudes H from 12.57 to 26.8, corresponding to diameters from about 10 m to about 10 km. The sample contains a variety of taxonomic types and physically or dynamically interesting objects. Among them, we have identified 5 binary asteroids and 20 tumblers (i.e., asteroids in excited, non-principal axis rotation states). Rotation periods of the characterized asteroids range from 1.45 min to 280 h, reflecting diversity of their properties and formation/evolution paths. We will present an overview of the data set and highlight several representative cases.

Petr Pravec↗

Ultra low density biodegradable shape memory polymer foams with tunable physical properties

Compositions and/or structures of degradable shape memory polymers (SMPs) ranging in form from neat/unfoamed to ultra low density materials of down to 0.005 g/cc density. These materials show controllable degradation rate, actuation temperature and breadth of transitions along with high modulus and excellent shape memory behavior. A method of m ly low density foams (up to 0.005 g/cc) via use of combined chemical and physical aking extreme blowing agents, where the physical blowing agents may be a single compound or mixtures of two or more compounds, and other related methods, including of using multiple co-blowing agents of successively higher boiling points in order to achieve a large range of densities for a fixed net chemical composition. Methods of optimization of the physical properties of the foams such as porosity, cell size and distribution, cell openness etc. of these materials, to further expand their uses and improve their performance.

36 MATERIALS SCIENCE↗

Research Opportunities in the Physical Design Optimization of Hybrid Power Plants: Preprint

With renewable energy growing to 10%-20% or more of overall electricity generation, design objectives for renewable power plants are shifting from producing energy at the lowest levelized cost to maximizing profitability. Several research and commercial efforts have investigated how to size respective generation and storage assets together for hybrid power plant systems - including wind, solar, battery storage and other technologies. However, the physical design of hybrid power plants has yet to be considered in detail. Even the design of individual solar and wind power plants is complex with large numbers of design variables, constraints and complex physical interactions across subsystems. Developing an integrated approach for the design of hybrid power plants including multiple generation technologies compounds this complexity and requires domain knowledge across the technologies as well as new approaches for addressing the statistical representation of resource availability and revenue opportunities. To inform the research needs on physical design of these hybrid power plants, a workshop was held in December 2018 at the National Renewable Energy Laboratory. This paper provides a summary of findings from the workshop on research needs for hybrid power plant design.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Cyber physical attack detection

A cyber-security threat detection system and method stores physical data measurements from a cyber-physical system and extracts synchronized measurement vectors synchronized to one or more timing pulses. The system and method synthesizes data integrity attacks in response to the physical data measurements and applies alternating parametrized linear and non-linear operations in response to the synthesized data integrity attacks. The synthesis renders optimized model parameters used to detect multiple cyber-attacks.

97 MATHEMATICS AND COMPUTING↗