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NASA NTRS1992

Availability of hydrogen for lunar base activities

Hydrogen will be needed on a lunar base to make water for consumables, to provide fuel, and to serve as a reducing agent in the extraction of oxygen from lunar minerals. This study was undertaken in order to learn more about the abundance and distribution of solar-wind-implanted hydrogen. Hydrogen was found in all samples studied, with concentrations, varying widely depending on soil maturity, grain size, and mineral composition. Seven cores returned from the Moon were studied. Although hydrogen was implanted in the upper surface layer of the regolith, it was found throughout the cores due to micrometeorite reworking of the soil.

Bustin, Roberta↗

NASA NTRS2004

Applications of Intelligent Tutoring Systems to Human-Robotic Exploration of Mars

Space missions with small crews extending over several years with time-delay preventing normal conversations with people on earth will raise many challenges for training. Of special interest are possible three-year missions to Mars, requiring refresher instruction and learning new skills based on unexpected problems with machines and environmental conditions. For example, the crew will be required to monitor and repair more complex life support systems for air and water recycling than we even know how to build today. Highly educated astronauts, often with several doctorate degrees, require a very different mode of interaction than we have developed for school children or even typical college students. Explanation methods may need to differ-using analogies and techniques from different domains-depending on whether the astronaut is an astrophysicist, a pilot, or a geologist.Virtual reality (e.g., for Hubble repair missions) and "integrated" simulations (involving role-playing and emphasizing failure scenarios) are the most common advanced forms of instruction used in space flight today. The emphasis is on collaborative, embodied interaction with the same workstations and tools used in practice (e.g., a cockpit simulator). Otherwise, computerized instructional technology used by NASA is not model-based or tutorial in nature. This discussion will review some of the key instructional methods used at NASA over the past two decades and consider why ITS methods have not been exploited. Some of the problems and opportunities for training for Mars missions are examined, including how using robots in exploration activities will help but raise new training problems. These ideas will be illustrated with examples from the BrahmsVE system in which a browser- based virtual reality display with avatars allows interacting with a distributed multiagent system, in which agents can be people, robots, or software programs. Using BrahmsVE may provide a way for astronauts to interact with proxies of people who serve as instructional coaches on Mars.

Clancey, William J.↗

NASA NTRS2006

Biologically-Inspired Concepts for Autonomic Self-Protection in Multiagent Systems

Biologically-inspired autonomous and autonomic systems (AAS) are essentially concerned with creating self-directed and self-managing systems based on metaphors &om nature and the human body, such as the autonomic nervous system. Agent technologies have been identified as a key enabler for engineering autonomy and autonomicity in systems, both in terms of retrofitting into legacy systems and in designing new systems. Handing over responsibility to systems themselves raises concerns for humans with regard to safety and security. This paper reports on the continued investigation into a strand of research on how to engineer self-protection mechanisms into systems to assist in encouraging confidence regarding security when utilizing autonomy and autonomicity. This includes utilizing the apoptosis and quiescence metaphors to potentially provide a self-destruct or self-sleep signal between autonomic agents when needed, and an ALice signal to facilitate self-identification and self-certification between anonymous autonomous agents and systems.

Sterritt, Roy↗

NASA NTRS2022

Contribution of Spicules to Solar Coronal Emission

Recent high-resolution imaging and spectroscopic observations have generated renewed interest in spicules' role in explaining the hot corona. Some studies suggest that some spicules, often classified as type II, may provide significant mass and energy to the corona. Here we use numerical simulations to investigate whether such spicules can produce the observed coronal emission without any additional coronal heating agent. Model spicules consisting of a cold body and hot tip are injected into the base of a warm (0.5 MK) equilibrium loop with different tip temperatures and injection velocities. Both piston- and pressure-driven shocks are produced. We find that the hot tip cools rapidly and disappears from coronal emission lines such as Fe xii 195 and Fe xiv 274. Prolonged hot emission is produced by preexisting loop material heated by the shock and by thermal conduction from the shock. However, the shapes and Doppler shifts of synthetic line profiles show significant discrepancies with observations. Furthermore, spatially and temporally averaged intensities are extremely low, suggesting that if the observed intensities from the quiet Sun and active regions were solely due to type II spicules, one to several orders of magnitude more spicules would be required than have been reported in the literature. This conclusion applies strictly to the ejected spicular material. We make no claims about emissions connected with waves or coronal currents that may be generated during the ejection process and heat the surrounding area.

Shanwlee Sow Mondal↗

DOE OSTI2023

IACMI Project 4.7: Pultruded Textile Carbon Fiber for Spar Caps (Final Report)

The primary objective of this project was to demonstrate the potential to significantly reduce the cost of wind turbine blades with carbon fiber reinforced polymer (CFRP) structure. Applicability of textile carbon fibers (TCF) were evaluated for use in pultruded spar cap (SC) elements as a path to cost reduction for utility scale wind turbine blades. In earlier work for the Department of Energy (DOE) Wind Energy Technologies Office (WETO), a collaboration of Sandia National Laboratory (SNL), Oak Ridge National Laboratory (ORNL), and Montana State University has demonstrated potential for pultruded TCF to compete with infused fiberglass and commercially available carbon fiber pultruded sections for spar cap construction. In the design cases evaluated, the TCF sections fared well when compared on cost per unit composite stiffness and cost per unit composite compressive strength for those designs [1]. Both stiffness and compressive strength tend to be key factors in the design of blade composite Spar Cap which carry the bulk of the blade structural loads in bending. Spar Cap design tends to distribute largely symmetric tensile and compressive stresses to opposite sides of the spar structure, but since carbon fiber composite compressive strength is typically 20-50% lower than tensile strength, the compressive loading reaches failure levels well before the tensile loading. Stiffness is critical in containing the large tip deflection in high wind loading situations. However, materials and process development were very limited in the earlier study and the work in this project was expanded to make the comparative information more representative of what will be required in order to make further inroads towards implementation. Similar to that study, this project team confirmed that the primary materials of interest for pultruded spar cap elements should be thermoset (TS) resins reinforced by carbon fibers, utilizing as high a percentage of TCF as practical to benchmark cost and performance against commercial carbon fibers. To make the closest comparison possible and eliminate specific test article size, resin selection, and equipment/operational nuance effects, the team planned to pultrude sections with 100% commercially available carbon fiber (Panex 35 carbon fiber from Zoltek) as well as samples utilizing high fractions of TCF. The resin system chosen was based on formulations recommended by large wind industry supplier Hexion and consisted of Hexion resin RSL-4597, curing agent CCA-138, and internal mold release additive 117, along with common kaolin filler ASP400P from BASF. As commonly deployed in spar cap configurations, the team had a mold built to pultrude a rectangular spar cap element of 100mm width and 3mm thickness. The extremely limited number of samples produced for the earlier study were produced with a “generic” epoxy utilized for a variety of applications by the pultruder contracted to produce test articles for demonstration purposes. More importantly, those samples were produced at a fiber fraction only slightly over 50%. Based on feedback from our industrial advisory team for that project and strongly recommended by this project team, the consensus is that it is highly desirable to obtain fiber fractions of 65-68% for significant penetration in wind blade spar cap. Although this requirement has yet to be exhaustively confirmed in readily available information, this was established as a project goal and informally decided we needed to exceed 60% fiber fraction to gain serious industry consideration. Previous TCF pultrusion trials have been challenged by the lack of robust TCF packages, resulting in non-uniform tension across and between tows, as well as excess labor and waste for removal of interleaved paper. The non-uniform tension and associated intermingling of tows in textile acrylic fiber tows and associated difficulties created from broken filaments in carbon fiber conversion inhibit the ordered packing necessary to enhance fiber fraction elevation. (These “cross-overs” are not considered undesirable for textile applications and there is some sense that they might be advantageous for those applications). In addition to work that is ongoing at the acrylic fiber manufacturers to improve their formats, The Institute of Advanced Composites Manufacturing Innovation (IACMI) Project 6.12 (report PA16-0349-6.12-01) [2] has developed and demonstrated a more robust packaging and creeling approach that at least partially addresses these issues, thus improving control of the TCF feed into the pultrusion unit. It was hoped that these and other improvements currently being implemented would allow us to achieve fiber fractions at least approaching these fiber fraction targets. During this project, sections utilizing 100% commercially available carbon fiber reinforcement were produced as a baseline, as well as sections reinforced with about 94% TCF and the balance being commercially available fiber for comparison. The most important finding was that similar to results reported in the earlier WETO-funded project and results from tests of TCF reported at IACMI meetings, this work demonstrated that sections pultruded with TCF in an epoxy resin frequently utilized in actual spar cap production had stiffness and compressive strengths largely comparable to similar sections pultruded with a commercially available carbon fiber also frequently utilized in the wind industry. Although the amount of that data is limited, some of the tensile strength results were actually closer than would have been expected based on fiber strength results provided by the TCF and commercial fiber producers. The actual test data are reported and discussed in detail in Section 5. The pultruded sections dominated by TCF reinforcement were approximately 8-10% lower in fiber fraction than for the sections produced using commercial fiber alone, making direct comparison difficult. The COVID-19 project has provided significant insight into the current state-of-the-art with various TCF product forms. The data obtained in this project will guide the planned improvements at the precursor level, especially in attaining uniform tensioning and payout to facilitate enhanced fiber fractions and overall processability of the TCF composites. The project team is providing guidance to stakeholders concerning the attributes, needs, and potential demand for TCF in wind blade spar caps. Results achieved in this project are consistent with findings in the related work cited [1] and support this guidance and the high potential for this product type. TCF precursor-producing partners continue to express interest in enhancing their product forms and the team looks forward to working with these improved materials as they become available.

42 ENGINEERING↗

NASA NTRS1989

A development framework for distributed artificial intelligence

The authors describe distributed artificial intelligence (DAI) applications in which multiple organizations of agents solve multiple domain problems. They then describe work in progress on a DAI system development environment, called SOCIAL, which consists of three primary language-based components. The Knowledge Object Language defines models of knowledge representation and reasoning. The metaCourier language supplies the underlying functionality for interprocess communication and control access across heterogeneous computing environments. The metaAgents language defines models for agent organization coordination, control, and resource management. Application agents and agent organizations will be constructed by combining metaAgents and metaCourier building blocks with task-specific functionality such as diagnostic or planning reasoning. This architecture hides implementation details of communications, control, and integration in distributed processing environments, enabling application developers to concentrate on the design and functionality of the intelligent agents and agent networks themselves.

Adler, Richard M.↗

NASA NTRS2004

Evaluation of CO2, N2 and He as Fire Suppression Agents in Microgravity

The U.S. modules of the International Space Station use gaseous CO2 as the fire extinguishing agent. This was selected as a result of extensive experience with CO2 as a fire suppressant in terrestrial applications, trade studies on various suppressants, and experiments. The selection of fire suppressants and suppression strategies for NASA s Lunar and Martian exploration missions will be based on the same studies and normal-gravity data unless reduced gravity fire suppression data is obtained. In this study, the suppressant agent concentrations required to extinguish a flame in low velocity convective flows within the 20-sec of low gravity on the KC-135 aircraft were investigated. Suppressant gas mixtures of CO2, N2, and He with the balance being oxygen/nitrogen mixtures with either 21% or 25% O2 were used to suppress flames on a 19-mm diameter PMMA cylinder in reduced gravity. For each of the suppressant mixtures, limiting concentrations were established that would extinguish the flame at any velocity. Similarly, concentrations were established that would not extinguish the flame. The limiting concentrations were generally consistent with previous studies but did suggest that geometry had an effect on the limiting conditions. Between the extinction and non-extinction limits, the suppression characteristics depended on the extinguishing agent, flow velocity, and O2 concentration. The limiting velocity data from the CO2, He, and N2 suppressants were well correlated using an effective mixture enthalpy per mole of O2, indicating that all act via O2 displacement and cooling mechanisms. In reduced gravity, the agent concentration required to suppress the flames increased as the velocity increased, up to approximately 10 cm/s (the maximum velocity evaluated in this experiment). The effective enthalpy required to extinguish flames at velocities of 10 cm/s is approximately the same as the concentrations in normal gravity. A computational study is underway to further evaluate these findings.

Ruff, Gary A.↗

DOE OSTI2025

An analysis of physics limited dispatch of nuclear renewable integrated energy systems using deep reinforcement learning and dynamic modeling

Previous approaches to dispatching nuclear integrated energy systems (NIES) have focused on the profitability and flexibility of these systems to operate on energy grids with highly variable pricing. However, due to the complexity involved in modeling and designing these systems, there has been less emphasis on ensuring that these dispatch strategies are physically achievable. It is imperative to develop methods that allow the system to remain within the desired NIES operating conditions and perform this based on realistic limited forecasted information. This research employs next generation artificial intelligence, namely deep reinforcement learning (DRL), and a dynamic system model written in Modelica to find a safe and profitable dispatch strategy for a solar nuclear hybrid design. The DRL agent is shown to find a novel dispatch strategy that manages both power ramping and power levels while respecting operational limits. This DRL-based dispatch is compared to other dispatching strategies including an optimal design solution from mixed integer linear programming (MILP). It is found that incorporating the physics of such a tightly coupled NIES limits the profitability of the MILP-based dispatch strategy. As a result, the MILP solution overestimates the design’s generated revenue. In contrast, DRL significantly reduces the number of breaches of safe operational conditions during energy arbitrage while maintaining profitability. Furthermore, this work paves the way for a more detailed assessment of NIES profitability and could be used to aid operator decisions on future NIES projects.

14 - SOLAR ENERGY↗

DOE OSTI2023

Drug discovery efforts at George Mason University

With over 39,000 students, and research expenditures in excess of $200 million, George Mason University (GMU) is the largest R1 (Carnegie Classification of very high research activity) university in Virginia. Mason scientists have been involved in the discovery and development of novel diagnostics and therapeutics in areas as diverse as infectious diseases and cancer. Below are highlights of the efforts being led by Mason researchers in the drug discovery arena. To enable targeted cellular delivery, and non-biomedical applications, Veneziano and colleagues have developed a synthesis strategy that enables the design of self-assembling DNA nanoparticles (DNA origami) with prescribed shape and size in the 10 to 100 nm range. The nanoparticles can be loaded with molecules of interest such as drugs, proteins and peptides, and are a promising new addition to the drug delivery platforms currently in use. The investigators also recently used the DNA origami nanoparticles to fine tune the spatial presentation of immunogens to study the impact on B cell activation. These studies are an important step towards the rational design of vaccines for a variety of infectious agents. To elucidate the parameters for optimizing the delivery efficiency of lipid nanoparticles (LNPs), Buschmann, Paige and colleagues have devised methods for predicting and experimentally validating the pKa of LNPs based on the structure of the ionizable lipids used to formulate the LNPs. These studies may pave the way for the development of new LNP delivery vehicles that have reduced systemic distribution and improved endosomal release of their cargo post administration. To better understand protein-protein interactions and identify potential drug targets that disrupt such interactions, Luchini and colleagues have developed a methodology that identifies contact points between proteins using small molecule dyes. The dye molecules noncovalently bind to the accessible surfaces of a protein complex with very high affinity, but are excluded from contact regions. When the complex is denatured and digested with trypsin, the exposed regions covered by the dye do not get cleaved by the enzyme, whereas the contact points are digested. The resulting fragments can then be identified using mass spectrometry. The data generated can serve as the basis for designing small molecules and peptides that can disrupt the formation of protein complexes involved in disease processes. For example, using peptides based on the interleukin 1 receptor accessory protein (IL-1RAcP), Luchini, Liotta, Paige and colleagues disrupted the formation of IL-1/IL-R/IL-1RAcP complex and demonstrated that the inhibition of complex formation reduced the inflammatory response to IL-1B. Working on the discovery of novel antimicrobial agents, Bishop, van Hoek and colleagues have discovered a number of antimicrobial peptides from reptiles and other species. DRGN-1, is a synthetic peptide based on a histone H1-derived peptide that they had identified from Komodo Dragon plasma. DRGN-1 was shown to disrupt bacterial biofilms and promote wound healing in an animal model. The peptide, along with others, is being developed and tested in preclinical studies. Other research by van Hoek and colleagues focuses on in silico antimicrobial peptide discovery, screening of small molecules for antibacterial properties, as well as assessment of diffusible signal factors (DFS) as future therapeutics. The above examples provide insight into the cutting-edge studies undertaken by GMU scientists to develop novel methodologies and platform technologies important to drug discovery.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2005

Intelligent Information Fusion in the Aviation Domain: A Semantic-Web based Approach

Information fusion from multiple sources is a critical requirement for System Wide Information Management in the National Airspace (NAS). NASA and the FAA envision creating an "integrated pool" of information originally coming from different sources, which users, intelligent agents and NAS decision support tools can tap into. In this paper we present the results of our initial investigations into the requirements and prototype development of such an integrated information pool for the NAS. We have attempted to ascertain key requirements for such an integrated pool based on a survey of DSS tools that will benefit from this integrated pool. We then advocate key technologies from computer science research areas such as the semantic web, information integration, and intelligent agents that we believe are well suited to achieving the envisioned system wide information management capabilities.

Ashish, Naveen↗

DOE OSTI2022

An Aluminum-Based Metal–Organic Cage for Cesium Capture

Metal–organic cages are a class of supramolecular structures that often require the careful selection of organic linkers and metal nodes. Of this class, few examples of metal–organic cages exist where the nodes are composed of main group metals. Herein, we have prepared an aluminum-based metal–organic cage, H 8 [Al 8 (pdc) 8 (OAc) 8 O 4 ] (Al-pdc-AA), using inexpensive and commercially available materials. The cage formation was achieved via solvothermal self-assembly of solvated aluminum and pyridine-dicarboxylic linkers in the presence of a capping agent, acetic acid. The obtained supramolecular structure was characterized by single-crystal X-ray diffraction (SCXRD), thermogravimetric analysis, and NMR spectroscopy. Based on crystal structure and computational analyses, the cage has a 3.7 Å diameter electron-rich cavity suitable for the binding of cations such as cesium (ionic radius of 1.69 Å). Here, the host–guest interactions were probed with 1 H and 133 Cs NMR spectroscopy in DMSO, where at low concentrations, Cs + binds to Al-pdc-AA in a 1:1 ratio. The binding site was identified from the crystal structure of CsH 7 [Al 8 (pdc) 8 (OAc) 8 O 4 ] (Cs + Al-pdc-AA), and a binding affinity of ~10 6 –10 7 M –1 was determined from NMR titration experiments. The Al-pdc-AA showed improved selectivity for cesium binding over alkali metal cations (Cs + > Rb + > K + >> Na + ~ Li + ). Collectively, the study reports a novel aluminum cage that can serve as a promising host for efficient and selective cesium removal.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Rational Design of Methylated Triazine‐Based Linear Conjugated Polymers for Efficient CO 2 Photoreduction with Water

The development of semiconducting conjugated polymers for photoredox catalysis holds great promise for sustainable utilization of solar energy. In this work, a new family of porous methylated triazine‐based linear conjugated polymers is reported that enable efficient photoreduction of carbon dioxide (CO 2 ) with water (H 2 O) vapor, in the absence of any additional photosensitizer, sacrificial agents or cocatalysts. It is demonstrated that the key lies in the generation of methylated triazine linkages through a facile condensation reaction between benzamidine and acetic anhydride, which impedes the formation of conventional triazine‐based frameworks. It is also shown that regulating conjugated linear backbones with different lengths of electron‐donated benzyl units provides a facile means to modulate their optical properties and the exciton dissociation, thereby affording more long‐lived photogenerated charge carriers and boosting charge separation and transfer. A high‐performance carbon monoxide (CO) production rate of 218.9 µmol g −1 h −1 is achieved with ≈ 100% CO selectivity, which is accompanied by exceptional H 2 O oxidation to oxygen (O 2 ). It anticipates this new study will advance synthetic approaches toward polymeric semiconductors and facilitate new possibilities for triazine‐based conjugated polymers with promising potential in artificial photocatalysis.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Efficient learning of power grid voltage control strategies via model-based deep reinforcement learning

Here this article proposes a model-based deep reinforcement learning (DRL) method to design emergency control strategies for short-term voltage stability problems in power systems. Recent advances show promising results for model-free DRL-based methods in power systems control problems. But in power systems applications, these model-free methods have certain issues related to training time (clock time) and sample efficiency; both are critical for making state-of-the-art DRL algorithms practically applicable. DRL-agent learns an optimal policy via a trial-and-error method while interacting with the real-world environment. It is also desirable to minimize the direct interaction of the DRL agent with the real-world power grid due to its safety-critical nature. Additionally, the state-of-the-art DRL-based policies are mostly trained using a physics-based grid simulator where dynamic simulation is computationally intensive, lowering the training efficiency. We propose a novel model-based DRL framework where a deep neural network (DNN)-based dynamic surrogate model (SM), instead of a real-world power grid or physics-based simulation, is utilized within the policy learning framework, making the process faster and more sample efficient. However, having stable training in model-based DRL is challenging because of the complex system dynamics of large-scale power systems. We addressed these issues by incorporating imitation learning to have a warm start in policy learning, reward-shaping, and multi-step loss in surrogate model training. Finally, we achieved 97.5% reduction in samples and 87.7% reduction in training time for an application to the IEEE 300-bus test system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2011

Operation Evaluation of the VEGGIE Food Production System in the Habitat Demonstration Unit

The 2010 Desert Research and Technology Studies (DRATS) of the VEGGIE Food Production System in the Habitat Demonstration Unit (HDU) Pressurized Excursion Module (PEM) was the first operational evaluation of salad crop production technology in a NASA analog test. A systematic evaluation of rooting media and nutrient delivery systems were evaluated for three lettuce cultivars that have shown promise as candidates for a surface based food production system. The VEGGIE nutrient delivery system worked well, was able to be maintained by multiple operators with a minimum of training, and supported excellent lettuce growth for the duration of the test. A Hazard Analysis and Critical Control Point (HACCP) evaluation was performed using ProSantm as sanitation agent prior to consumption was approved, and the crew was allowed to consume the lettuce grown using the VEGGIE light cap and gravity based nutrient delivery system at the completion of the 14-day DRAT field test. The DRAT field test validated the crew operations; Growth of all lettuce cultivars was excellent. The operational DRAT field testing in the HDU identified light quality issues related to morphology and pigment development that will need to be addressed through additional testing. Feedback from the crew, ground support personnel, and human factors leads was uniformly positive on the psychological value of having the crop production system in the excursion module. A number of areas have been identified for future work, to minimize the "footprint" of the Food Production system through creative use of unused wall and floor space in the unit.

Stutte, Gary W.↗

DOE OSTI2021

Rubik’s Cube Topology Based Particle Swarm Algorithm 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, stabilizing the main power grid, etc. 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. In addition, 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, Rubiks 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 Rubiks 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.

Feng, Xiaochun↗

DOE OSTI2023

Multi-Agent Reinforcement Learning for Distribution System Critical Load Restoration

Grid resilience has become a critical topic recently because of the increasing occurrence of extreme events and the growing integration of intermittent renewable energy sources. To build a resilient distribution system, this paper develops a multiagent reinforcement learning-based (MARL) method to coordinate distribution energy resources (DERs) dispatch, load pickup, and network reconfiguration for load restoration after a system outage. With the help of two types of control agents, namely critical load restoration (CLR) and coordination (COR) agents, system loads can be restored efficiently, given available resources. The effectiveness and superiority of the proposed algorithm are demonstrated through simulations and comparative studies on a real distribution feeder in Western Colorado.

distribution system↗

NASA NTRS2011

Operational Evaluation of VEGGIE Food Production System in the Habitat Demonstration Unit

The 2010 Desert Research and Technology Studies (DRATS) of the VEGGIE Food Production System in the Habitat Demonstration Unit (HDU) Pressurized Excursion Module (PEM) was the first operational evaluation of salad crop production technology in a NASA analog test. A systematic evaluation of rooting media and nutrient delivery systems were evaluated for three lettuce cultivars that have shown promise as candidates for a surface based food production system. The VEGGIE nutrient delivery system worked well, was able to be maintained by multiple operators with a minimum of training, and supported excellent lettuce growth for the duration of the test. A Hazard Analysis and Critical Control Point (HACCP) evaluation was performed using ProSan(tm) as sanitation agent prior to consumption was approved, and the crew was allowed to consume the lettuce grown using the VEGGIE light cap and gravity based nutrient delivery system at the completion of the 14-day DRAT field test. The DRAT field test validated the crew operations; Growth of all lettuce cultivars was excellent. The operational DRAT field testing in the HDU identified light quality issues related to morphology and pigment development that will need to be addressed through additional testing. Feedback from the crew, ground support personnel, and human factors leads was uniformly positive on the psychological value of having the crop production system in the excursion module. A number of areas have been identified for future work, to minimize the "footprint" of the Food Production system through creative use of unused wall and floor space in the unit.

Stutte, Gary W.↗

DOE OSTI2021

Immobilization of transgenic plant cells towards bioprinting for production of a recombinant biodefense agent

Abstract Transgenic rice cells ( Oryza sativa ) producing recombinant butyrylcholinesterase (BChE) as a prophylactic/therapeutic against organophosphate nerve agent poisoning, cocaine toxicity, and neurodegenerative diseases like Alzheimer's were immobilized in a polyethylene glycol‐based hydrogel. The cells were sustained for 14 days in the semi‐solid matrix, undergoing a growth phase from days 0–6, a BChE production phase in sugar‐free medium from days 6–12, and a growth/recovery phase from days 12–14. Throughout this period, the cells maintained similar viability to those in suspension cultures and displayed analogous sugar consumption trends. The rice cells in the hydrogel also produced a significant amount of active BChE, comparable to the levels produced in liquid cultures. A considerable fraction of this BChE was secreted into the media, allowing for easier product separation. To the best of our knowledge, this proof‐of‐concept is the first report of immobilization of recombinant plant cells for continuous production of high‐value heterologous proteins. This work serves as a foundation for further investigation towards plant cell bioprinting and the development of a simple, efficient, robust, modular, and potentially field‐deployable bioreactor system for the manufacture of biologics.

Varma, Anika↗