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At least 415 records · Page 23

Ultrasonic Characterization of Ethylene Vinyl Acetate (EVA) Crosslinking for Quality Assurance and Lamination Process Control (US-Xlink)

Module makers strive to cut lamination processing times to enhance production throughput and reduce costs. If overdone, this might lead to poor EVA quality due to incomplete EVA crosslinking and a large concentration of potentially harmful reactants. Those deficiencies are frequently missed during production quality testing as initially their impact on power output is small. Additionally, the crosslinking agent is frequently inhomogeneously dispersed across the EVA foils such that local destructive characterization procedures such as differential scanning calorimetry (DSC), Soxhlet extraction, swelling methods, or mechanical tests provide only a limited amount of information. However, these defects and inhomogeneities can become considerably more important during field operation, dramatically reducing long-term power yield, and increasing LCOE. Examples of typical long-term module degradation modes relating to poor lamination process conditions include cell breakage, corrosion of the metallization, delamination, and local quality deficiencies. To provide reliable material characterization in a manufacturing setting, we devised a non-destructive technology that uses ultrasound to evaluate the quality of interface adhesion and the degree of crosslinking. As a calibration reference, DSC measurements were employed. Although the potential of ultrasonic approaches for this purpose has already been noted, those previous methods were generally limited to local qualitative measurements. Furthermore, variations in EVA thickness and temperature had a substantial impact on them. The solution we propose solves these limitations by employing ultrasonic absorption rather than relying solely on sound velocity data.

14 SOLAR ENERGY↗

Structure, Hydrodynamics, and Phase Transition of Freely Suspended Liquid Crystals

Smectic liquid crystals are phases of rod shaped molecules organized into one dimensionally (1D) periodic arrays of layers, each layer being between one and two molecular lengths thick. In the least ordered smectic phases, the smectics A and C, each layer is a two dimensional (2D) liquid. Additionally there are a variety of more ordered smectic phases having hexatic short range translational order or 2D crystalline quasi long range translational order within the layers. The inherent fluid-layer structure and low vapor pressure of smectic liquid crystals enable the long term stabilization of freely suspended, single component, layered fluid films as thin as 30A, a single molecular layer. The layering forces the films to be an integral number of smectic layers thick, quantizing their thickness in layer units and forcing a film of a particular number of layers to be physically homogeneous with respect to its layer structure over its entire area. Optical reflectivity enables the precise determination of the number of layers. These ultrathin freely suspended liquid crystal films are structures of fundamental interest in condensed matter and fluid physics. They are the thinnest known stable condensed phase fluid structures and have the largest surface-to-volume ratio of any stable fluid preparation, making them ideal for the study of the effects of reduced dimensionality on phase behavior and on fluctuation and interface phenomena. Their low vapor pressure and quantized thickness enable the effective use of microgravity to extend the study of basic capillary phenomena to ultrathin fluid films. Freely suspended films have been a wellspring of new liquid crystal physics. They have been used to provide unique experimental conditions for the study of condensed phase transitions in two dimensions. They are the only system in which the hexatic has been unambiguously identified as a phase of matter, and the only physical system in which fluctuations of a 2D XY system and Kosterlitz Thouless phase transition has been observed and 2D XY quasi long range order verified. Smectic films have enabled the precise determination of smectic layer electron density and positional fluctuation profile and have been used to show that the interlayer interactions in anti-ferroelectric tilted smectics do not extend significantly beyond nearest neighbors. The interactions which are operative in liquid crystals are generally weak in comparison to those in crystalline phases, leading to the facile manipulation of the order in liquid crystals by external agents such as applied fields and surfaces. Effects arising from weak ordering are significantly enhanced in ultrathin free films and filaments wherein the intermolecular coupling is effectively reduced by loss of neighbors. Over the past four years this research, which we now detail, has produced a host of exciting new discoveries and unexpected results, maintaining the position of the study of freely suspended liquid crystal structures as one of most exciting and fruitful areas of complex fluid physics. In addition, several potentially interesting microgravity free film experiments have been identified.

Clark, Noel A.↗

Deletion of the H240R Gene in African Swine Fever Virus Partially Reduces Virus Virulence in Swine

African swine fever (ASF) is a highly contagious disease that affects wild and domestic swine. Currently, the disease is present as a pandemic affecting pork production in Eurasia and the Caribbean region. The etiological agent of ASF is a large, highly complex structural virus (ASFV) harboring a double-stranded genome encoding for more than 160 proteins whose functions, in most cases, have not been experimentally characterized. We show here that deletion of the ASFV gene H240R from the genome of the highly virulent ASFV-Georgia2010 (ASFV-G) isolate partially decreases virus virulence when experimentally inoculated in domestic swine. ASFV-G-ΔH240R, a recombinant virus harboring the deletion of the H240R gene, was produced to evaluate the function of the gene in the development of disease in pigs. While all animals intramuscularly inoculated with 10 2 HAD 50 of ASFV-G developed a fatal form of the disease, forty percent of pigs receiving a similar dose of ASFV-G-ΔH240R survived the infection, remaining healthy during the 28-day observational period, and the remaining sixty percent developed a protracted but fatal form of the disease compared to that induced by ASFV-G. Additionally, all animals inoculated with ASFV-G-ΔH240R presented protracted viremias with reduced virus titers when compared with those found in animals inoculated with ASFV-G. Animals surviving infection with ASFV-G-ΔH240R developed a strong virus-specific antibody response and were protected against the challenge of the virulent parental ASFV-G.

59 BASIC BIOLOGICAL SCIENCES↗

Soft Actor Critic Based Volt-VAR Co-optimization in Active Distribution Grids

Modern distribution networks are undergoing several technical challenges, such as voltage fluctuations, because of high penetration of distributed energy resources (DERs). This paper proposes a deep reinforcement learning (DRL)-based Volt VAR co-optimization technique for reducing voltage fluctuations as well as power loss under high penetration of DERs. In addition, the proposed approach minimizes the operational cost of the grid. A stochastic policy optimization based soft actor critic (SAC) agent is proposed to configure the optimal set-points of the reactive power outputs of the inverters. The performance of the proposed model is verified on the modified IEEE 34- and 123-bus systems and compared with a base case scenario with no reactive supply by inverters, and a local droop control approach. The results demonstrate that the proposed framework outperforms the conventional droop control method in improving the voltage profile, minimizing the network power loss, and reducing grid operational cost.

—Distribution grids, deep reinforcement learning, ↗

Variational multiscale reinforcement learning for discovering reduced order closure models of nonlinear spatiotemporal transport systems

Abstract A central challenge in the computational modeling and simulation of a multitude of science applications is to achieve robust and accurate closures for their coarse-grained representations due to underlying highly nonlinear multiscale interactions. These closure models are common in many nonlinear spatiotemporal systems to account for losses due to reduced order representations, including many transport phenomena in fluids. Previous data-driven closure modeling efforts have mostly focused on supervised learning approaches using high fidelity simulation data. On the other hand, reinforcement learning (RL) is a powerful yet relatively uncharted method in spatiotemporally extended systems. In this study, we put forth a modular dynamic closure modeling and discovery framework to stabilize the Galerkin projection based reduced order models that may arise in many nonlinear spatiotemporal dynamical systems with quadratic nonlinearity. However, a key element in creating a robust RL agent is to introduce a feasible reward function, which can be constituted of any difference metrics between the RL model and high fidelity simulation data. First, we introduce a multi-modal RL to discover mode-dependant closure policies that utilize the high fidelity data in rewarding our RL agent. We then formulate a variational multiscale RL (VMRL) approach to discover closure models without requiring access to the high fidelity data in designing the reward function. Specifically, our chief innovation is to leverage variational multiscale formalism to quantify the difference between modal interactions in Galerkin systems. Our results in simulating the viscous Burgers equation indicate that the proposed VMRL method leads to robust and accurate closure parameterizations, and it may potentially be used to discover scale-aware closure models for complex dynamical systems.

97 MATHEMATICS AND COMPUTING↗

Electrochemistry of lunar rocks

Electrolysis of silicate melts has been shown to be an effective means of producing metals from common silicate materials. No fluxing agents need be added to the melts. From solution in melts of diopside (CaMgSi2O6) composition, the elements Si, Ti, Ni, and Fe have been reduced to their metallic states. Platinum is a satisfactory anode material, but other cathode materials are needed. Electrolysis of compositional analogs of lunar rocks initially produces iron metal at the cathode and oxygen gas at the anode. Utilizing mainly heat and electricity which are readily available from sunlight, direct electrolysis is capable of producing useful metals from common feedstocks without the need for expendable chemicals. This simple process and the products obtained from it deserve further study for use in materials processing in space.

Lindstrom, D. J.↗

Autonomous Agents and Intelligent Assistants for Exploration Operations

Human exploration of space will involve remote autonomous crew and systems in long missions. Data to earth will be delayed and limited. Earth control centers will not receive continuous real-time telemetry data, and there will be communication round trips of up to one hour. There will be reduced human monitoring on the planet and earth. When crews are present on the planet, they will be occupied with other activities, and system management will be a low priority task. Earth control centers will use multi-tasking "night shift" and on-call specialists. A new project at Johnson Space Center is developing software to support teamwork between distributed human and software agents in future interplanetary work environments. The Engineering and Mission Operations Directorates at Johnson Space Center (JSC) are combining laboratories and expertise to carry out this project, by establishing a testbed for hWl1an centered design, development and evaluation of intelligent autonomous and assistant systems. Intelligent autonomous systems for managing systems on planetary bases will commuicate their knowledge to support distributed multi-agent mixed-initiative operations. Intelligent assistant agents will respond to events by developing briefings and responses according to instructions from human agents on earth and in space.

Malin, Jane T.↗

Intelligent Change Detection System: Autonomous Intelligent Machine Agent Model Development

NASA’s significant role in facilitating the harmonious integration of unmanned aircraft systems (UAS), with other aerial vehicles operating in the National Airspace System (NAS), has revealed a need for more advanced technological tools than are being utilized currently. This technology would lend itself to significantly assisting Direct-Action Aviation Personnel (DAAP) with the ingress and egress of UAS operations within the NAS. Providing research findings that would reduce technical barriers, associated with UAS-NAS integration, has been a persistent effort by both NASA and the FAA. One such research effort, pursued by NASA’s Transformative Tools and Technologies – Revolutionary Aviation Mobility (T3-RAM) project, is the development of an autonomous intelligent machine (AIM) agent that would aid DAAP functioning as implemented in remote ground control stations (RGCS). This evolution of the “human-machine” symbiosis, within the aviation environment, is necessary for many reasons. For example, there are projections of large increases to the 864,000 registered UAS and 45,000 aviation operations taking place in the NAS each day. With a data output range from 1 to 20 terabytes per flight or each aerial vehicle, which is projected to have proportional rate increase to that of registered UASs. It is evident, that due to the projected increase of UASs and their generated data, the human-agent’s data managing capabilities will be quickly overwhelmed by the enormous amounts of data emanating in the NAS. The research efforts presented in this paper puts forward results from the development, assessment, and verification of a previously conceptualized AIM-Agent that combats actionable-data (information) errors resulting from the visual perception phenomenon known as “change blindness” (CB). CB has been identified as one of the main culprits of information erroring encountered within the ground control station operator (GCSO) community.

Change Blindness↗

Presynthetic Redox Gated Metal-to-Insulator Transition and Photothermoelectric Properties in Nickel Tetrathiafulvalene-Tetrathiolate Coordination Polymers

Photothermoelectric (PTE) materials are promising candidates for solar energy harvesting and photodetection applications, especially for near-infrared (NIR) wavelengths. Although the processability and tunability of organic materials are highly advantageous, examples of organic PTE materials are comparatively rare and their PTE performance is typically limited by poor photothermal (PT) conversion. Here, we report the use of redox-active Sn complexes of tetrathiafulvalene-tetrathiolate (TTFtt) as transmetalating agents for the synthesis of presynthetically redox tuned NiTTFtt materials. Unlike the neutral material NiTTFtt, which exhibits n-type glassy-metallic conductivity, the reduced materials Li 1.2 Ni 0.4 [NiTTFtt] and [Li(THF) 1.5 ] 1.2 Ni 0.4 [NiTTFtt] (THF = tetrahydrofuran) display physical characteristics more consistent with p-type semiconductors. The broad spectral absorption and electrically conducting nature of these TTFtt-based materials enable highly efficient NIR-thermal conversion and good PTE performance. Furthermore, in contrast to conventional PTE composites, these NiTTFtt coordination polymers are notable as single-component PTE materials. As a result, the presynthetically tuned metal-to-insulator transition in these NiTTFtt systems directly modulates their PT and PTE properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Community-Based Transactive Coordination Mechanism for Enabling Grid Edge Systems

The changing landscape of the electricity industry, characterized by a surge in distributed energy resources (DERs) and proactive customers, necessitates practical solutions for coordinated operations especially at the distribution-level. This paper introduces a community-based transactive coordination mechanism designed to incentivize customers for providing localized and system-level services reflected through real-time prices. The work presents a bidding approach for communities with DERs, such as solar photovoltaic (PV) and battery energy storage systems (BESS), to formulate their price-responsiveness for retail energy coordination, emphasizing a community-centric model. By sending bidding curves to a third-party, the mechanism enables customers with DER assets to actively participate in localized coordination with the load serving entity (LSE), thereby supplementing each other’s and even the utilities needs through a shared energy economy. The proposed transactive mechanism is implemented leveraging a co-simulation framework that integrates a distribution grid simulator and Python-based agents for performance evaluation. Collaboration with a local utility to access real distribution feeder models and consumption profiles yields simulation results demonstrating the potential to reduce costs by 12\% for communities with DERs like PV and BESS.

Community-based coordination, grid-edge systems, R↗

Spatiotemporal Monitoring of Hydrilla [Hydrilla verticillata (L. f.) Royle] to Aid Management Actions

Hydrilla is an invasive aquatic plant that has rapidly spread through many inland water bodies across the globe by outcompeting native aquatic plants. Drinking water supply, power generation, and recreational use of lakes are threatened by the spread of this invasive species. Moreover, hydrilla serves as a host for an epiphytic, toxic cyanobacteria known to be the causative agent of the neurodegenerative disease called avian vacuolar myelinopathy, which affects waterfowl, raptors, and amphibians. The early detection of hydrilla infestation is very important to reduce the costs associated with control and removal efforts of this invasive species. Therefore, this study was aimed at developing a rapid, frequent, and large-scale tool for monitoring and predicting spatial extent of hydrilla habitat. This was achieved by integrating in situ and Landsat 8 OLI satellite data for Lake J. Strom Thurmond, the largest US Army Corps of Engineers Lake east of the Mississippi River located on the Georgia/South Caroline border. The predictive model incorporated remote sensing reflectance, Secchi disk depth (SDD), light attenuation coefficient (Kd), maximum depth of colonization (Zc), and percentage of light available through water column (PLW). The model predicted ideal habitat for hydrilla featuring high SDD, low values of Kd, high Zc and PLW. Final analysis showed that hydrilla starts growing in April, reaches peak around October, begins retreating in the following months, and disappears in February. Additionally, physical meteorological factors were analyzed and were found to be closely associated with hydrilla extent. Management agencies can use these results to not only to plan future removal efforts, but also evaluate and adapt their current mitigation efforts.

Percentage of light available through the water co↗

Towards Autonomous Lunar Resource Excavation via Reinforcement Learning

To continue on a sustainable and flexible path, NASA needs to address the challenge of collecting and moving large amounts of regolith at the destination. NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for In-Situ Resource Utilization (ISRU) processing. RASSOR’s design enables it to efficiently collect and deposit regolith, return collected material for processing, and myriad related ISRU activities. To reliably perform these operations on the lunar surface, RASSOR software and sensory systems need to be robust and maximize the information extracted from a reduced sensor payload. Herein, we present preliminary findings from the Intelligent Capabilities Enhanced RASSOR project. We created reduced-order simulation environments to develop autonomous trenching controllers via reinforcement learning and prototype state estimation architectures. The goal of reinforcement learning is for an agent to learn a policy (task strategy) through interactions with an environment. When the agent performs an action, a change occurs in environment state and a numerical reward is received which informs the agent whether the action performed was good or not. Since reinforcement learning algorithms learn through trial-and-error, a simulation is a desirable first environment for development and learning. We developed two simulations, the first is a 2D excavation simulation developed to facilitate parameter selection, and a 3D simulation developed using a game physics engine, to simulate simplified soil interactions and increase the fidelity of the dynamic models of the robotic agents. The development of this 3D simulation has enabled the training of additional sensing capabilities and research both at the granular mechanics and operations levels. We experimented with various virtual sensor payloads to identify a combination that enabled efficient excavation operation and learning. Our reward function is based on how much material is excavated per step. A penalty is also received for leaving the dig site and to smooth the acceleration of the drum arms. We implemented pseudo time-of-flight sensors to report distance from each drum to ground and the height above ground which was found to be more efficient than existing solutions. Our findings suggest that reinforcement learning for autonomous operations has learned viable trenching strategies within 3000 training episodes in our simplified 2D environment and helped identify desirable sensing capabilities, arrangements, and considerations such as the positioning of time-of-flight sensors. Future work includes expanding our simulation to more complex environments and scenarios, and transfer learning from simulation to RASSOR 2.0 hardware for deployment in the Regolith Test Bin at NASA's Kennedy Space Center.

rassor↗

Structure and Dynamics of Freely Suspended Liquid Crystals

Smectic liquid crystals are phases of rod shaped molecules organized into one dimensionally (1 D) periodic arrays of layers, each layer being between one and two molecular lengths thick. In the least ordered smectic phases, the smectics A and C, each layer is a two dimensional (2D) liquid. Additionally there are a variety of more ordered smectic phases having hexatic short range translational order or 2D crystalline or quasi long range translational order within the layers. The inherent fluid-layer structure and low vapor pressure of smectic liquid crystals enables the long term stabilization of freely suspended, single component, layered fluid films as thin as 30A, a single molecular layer. The layering forces the films to be an integral number of smectic layers thick, quantizing their thickness in layer units and forcing a film of a particular number of layers to be physically homogeneous with respect to its layer structure over its entire area. Optical reflectivity enables the precise determination of the number of layers. These ultrathin freely suspended liquid crystal films are structures of fundamental interest in condensed matter and fluid physics. They are the thinnest known stable fluid structures and have the largest surface-to-volume ratio of any stable fluid preparation, making them ideal for the study of the effects of reduced dimensionality on phase behavior and on fluctuation and interface phenomena. Their low vapor pressure and quantized thickness enable the effective use of microgravity to extend the study of basic capillary phenomena to ultrathin fluid films. Freely suspended films have been a wellspring of new LC physics. They have been used to provide unique experimental conditions for the study of condensed phase transitions in two dimensions. They are the only system in which the hexatic has been unambiguously identified as a phase of matter, and the only physical system in which fluctuations of a 2D XY system and Kosterlitz Thouless phase transition has been observed and 2D XY quasi long range order verified. Smectic films have enabled the precise determination of smectic layer electron density and positional fluctuation profiles and have been used to show that the interlayer interactions in antiferroelectric tilted smectics do not extend significantly beyond nearest neighbors. Freely suspended films played a pivotal role in the recent discovery of macroscopic chiral-polar ordering in fluids of achiral molecules. The interactions which are operative in liquid crystals are generally weak in comparison to those in crystalline phases, leading to the facile manipulation of the order in liquid crystals by external agents such as applied fields and surfaces. Effects arising from weak ordering are significantly enhanced in ultrathin free films and filaments, in which the intermolecular coupling is effectively further reduced by loss of neighbors. Over the past four years this research, which we now detail, has produced a host of exciting new discoveries and unexpected results, maintaining the study of freely suspended liquid crystal structures as one of most exciting and fruitful areas of complex fluid physics. In addition, a class of experiments on the behavior of 1D interfaces in 2D films have been pursued with results that point to potentially quite interesting effects in microgravity.

Clark, Noel A.↗

Flight Deck Surface Trajectory-Based Operations (STBO): A Four-Dimensional Trajectory (4DT) Simulation

Within human factors there is burgeoning interest in the Human-Autonomy Teaming (HAT) concept as away to address the challenges of interacting with complex, increasingly autonomous systems. The HAT concept comes out of an aspiration to interact with increasingly autonomous automation as a team member, rather than simply use automation as a tool. The authors, and others, have proposed core tenets for HAT that include bi-directional communication, automation and system transparency, and advanced coordination between human and automated teammates via predefined, dynamic task sequences known as plays (Shively et al., 2017). It is believed that, with proper implementation, HAT should foster appropriate teamwork, thus increasing trust and reliance on the system, which in turn will reduce workload, increase situation awareness, and improve performance. To this end, HAT has been demonstrated and/or studied in multiple applications including search and rescue operations (Nourbakhsh et al., 2005), healthcare and medicine (Tsui Yanco, 2007), autonomous vehicles (Parasuraman, Barnes, Cosenzo, Mulgund, 2007), photography (Lachter, Brandt, Sadler, Shively, in press), and aviation (Shively et al., in press). The current paper presents one such effort to apply HAT. It details the design of a R-HAT Agent developed as part of a NASA Research Agreement awarded to Human-Autonomy Teaming Solutions Inc. (HATS Inc), and developed in collaboration with the Human-Autonomy Teaming Laboratory at NASA Ames Research Center. The role of this Agent is to mediate interaction between the automation and the human operator of an advanced ground dispatch station, with this mediation based upon previously mentioned core tenets for HAT and the many lessons learned from the HAT research literature. This dispatch station was developed to support a NASA project investigating a concept called Reduced Crew Operations (RCO; Lachter, Brandt, Battiste, Matessa, Johnson, in press). Part of the RCO concept involves a ground operator providing enhanced support to a large number of aircraft with a single pilot on the flight deck. When assisted by the Agent, operators can monitor and support or manage a large number of aircraft and use plays to respond in real-time to complicated, workload-intensive events (e.g., an airport closure). A play is a plan that encapsulates goals, tasks, and a task allocation strategy appropriate for a particular situation. In the current implementation, when a play is initiated by a user, the Agent determines what tasks need to be done and has the ability to autonomously execute them (e.g., determining diversion options and uplinking new routes to aircraft) when it is safe and appropriate. The R-HAT Agent has been designed to both support end users and research in RCO and HAT. Additionally, the Agent and its underlying architecture were developed with generalizability in mind as a modular piece of software applicable outside of RCO aviation in domains such as those mentioned above. This paper will also discuss future further development and testing of the R-HAT Agent.

Bakowski, Deborah L.↗

Volt-VAR Optimization in Distribution Networks Using Twin Delayed Deep Reinforcement Learning

Modern distribution grids are undergoing new challenges due to the stochastic nature of distributed energy resources (DERs). High penetration of DERs has a significant impact on Volt-VAR profile and system power losses. This work proposes a deep reinforcement learning (DRL)-based Volt-VAR optimization approach for improving voltage profile and reducing system power loss under high penetration of distributed energy resources, such as battery energy storage and solar photovoltaic units in distribution grids. The twin delayed deep deterministic policy gradient (TD3) method-based DRL agent is proposed to configure optimal set-points of reactive power outputs of fast responding smart inverters. The agent schedules the reactive power of inverters according to their physical capabilities, such as minimum allowed power factor, e.g., 0.9 leading/lagging. The reward function of the proposed DRL scheme is designed carefully to ensure a proper voltage profile of the grids with effective scheduling of reactive power outputs from inverters. The performance of the proposed model is verified on modified IEEE 34- and 123-bus systems and compared with base case with no reactive supply by inverters, and local droop Volt-VAR control approach. The results show that the proposed method performs better than the local droop control and deep deterministic policy gradient (DDPG)-based DRL method for reducing voltage fluctuation and minimizing power loss.

Hossain, Rakib↗

Prospects for carbon-negative biomanufacturing

Biomanufacturing has the potential to reduce demand for petrochemicals and mitigate climate change. Recent studies have also suggested that some of these products can be net carbon negative, effectively removing CO 2 from the atmosphere and locking it up in products. This review explores the magnitude of carbon removal achievable through biomanufacturing and discusses the likely fate of carbon in a range of target molecules. Solvents, cleaning agents, or food and pharmaceutical additives will likely re-release their carbon as CO 2 at the end of their functional lives, while carbon incorporated into non-compostable polymers can result in long-term sequestration. Future research can maximize its impact by focusing on reducing emissions, achieving performance advantages, and enabling a more circular carbon economy.

59 BASIC BIOLOGICAL SCIENCES↗

Improved Particle Swarm Algorithm Using Rubik’s Cube Topology for Bilevel Building Energy Transaction

Following the rapid growth of distributed energy resources (e.g., renewables, battery), localized peer-to-peer energy transactions are receiving more attention for multiple benefits, such as reducing power loss and stabilizing the main power grid. To promote distributed renewables locally, the local trading price is usually set to be within the external energy purchasing and selling price range. Consequently, building prosumers are motivated to trade energy through a local transaction center. This local energy transaction is modeled in bilevel optimization game. A selfish upper level agent is assumed with the privilege to set the internal energy transaction price with an objective of maximizing its arbitrage profit. Meanwhile, the building prosumers at the lower level will response to this transaction price and make decisions on electricity transaction amount. Therefore, this non-cooperative leader-follower trading game is seeking for equilibrium solutions on the energy transaction amount and prices. Additionally, a uniform local transaction price structure (purchase price equals selling price) is considered here. Aiming at reducing the computational burden from classical Karush–Kuhn–Tucker (KKT) transformation and protecting the private information of each stakeholder (e.g., building), swarm intelligence-based solution approach is employed for upper level agent to generate trading price and coordinate the transactive operations. On one hand, to decrease the chance of premature convergence in global-best topology, Rubik’s Cube topology is proposed in this study based on further improvement of a two-dimensional square lattice model (i.e., one local-best topology-Von Neumann topology). Rotating operation of the cube is introduced to dynamically changing the neighborhood and enhancing information flow at the later searching state. Several groups of experiments are designed to evaluate the performance of proposed Rubik’s Cube topology-based particle swarm algorithm. The results have validated the effectiveness of proposed topology and operators comparing with global-best version PSO and Von Neumann topology-based PSO and its scalability on larger scale applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Dextroamphetamine: a pharmacologic countermeasure for space motion sickness and orthostatic dysfunction

Dextroamphetamine has potential as a pharmacologic agent for the alleviation of two common health effects associated with microgravity. As an adjuvant to Space Motion Sickness (SMS) medication, dextroamphetamine can enhance treatment efficacy by reducing undesirable Central Nervous System (CNS) side effects of SMS medications. Secondly, dextroamphetamine may be useful for the prevention of symptoms of post-mission orthostatic intolerance caused by cardiovascular deconditioning during spaceflight. There is interest in developing an intranasal delivery form of dextroamphetanmine for use as a countermeasure in microgravity conditions. Development of this dosage form will require an analytical detection method with sensitivity in the low ng range (1 to 100 ng/mL). During the 1995 Summer Faculty Fellowship Program, two analytical methods were developed and evaluated for their suitability as quantitative procedures for dextroamphetamine in studies of product stability, bioavailability assessment, and pharmacokinetic evaluation. In developing some of the analytical methods, beta-phenylethylamine, a primary amine structurally similar to dextroamphetamine, was used. The first analytical procedure to be evaluated involved hexane extraction and subsequent fluorescamine labeling of beta-phenylethylamine. The second analytical procedure to be evaluated involved quantitation of dextroamphetamine by an Enzyme-Linked ImmunoSorbent Assay (ELISA).

Snow, L. Dale↗