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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DER Translate

SAND2024-13723O This software translates and maps any .xlsx-based distributed energy resource (DER) device from the SunSpec certification registry (https://sunspec.org/certified-registry/) to a JSON-based DER models map. It is then read by DER monitoring tools for applications such as network intrusion detection and system health monitoring. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Fragkos, Georgios↗

Hypersonic research engine project. Phase 2: Some combustor test results of NASA aerothermodynamic integration model

Combustor test results of the NASA Aerothermodynamic Integration Model are presented of a ramjet engine developed for operation between Mach 3 and 8. Ground-based and flight experiments which provide the data required to advance the technology of hypersonic air-breathing propulsion systems as well as to evaluate facility and testing techniques are described. The engine was tested with synthetic air at Mach 5, 6, and 7. The hydrogen fuel was heated to 1500 R prior to injection to simulate a regeneratively cooled system. Combustor efficiencies up to 95 percent at Mach 6 were achieved. Combustor process in terms of effectiveness, pressure integral factor, total pressure recovery and Crocco's pressure-area relationship are presented and discussed. Interactions between inlet-combustor, combustor stages, combustor-nozzle, and the effects of altitude, combustor step, and struts are observed and analyzed.

Sun, Y. H.↗

Rotordynamic Analysis of the SSME Turbopumps Using Reduced Models

Alternative methods for the rotor-dynamic and sensitivity analysis of large rotor systems are examined. The methods are assessed for their ability to utilize accurate models of reduced size along with effective procedures for describing the dynamic behavior of the systems. Frequency response-based techniques are developed for determining the steady state response to imbalance of the space shuttle main engine (SSME) turbopumps and the related eigenvalue problem. The rotor and housing are represented by reduced receptances associated with their coupling points. The housing may be described by all of its normal modes within a frequency range of interest. The effects of truncated higher and lower modes are accounted for in an approximate manner. A procedure is described for determining the sensitivity of the coupling forces to changes in the coupling elements and rotor speed of the turbopump systems. In addition, an eigenvalue sensitivity analysis technique is adopted for application to the systems. Computer programs were developed for the numerical implementation of the impedance and eigenvalue sensitivity formulated in this study.

Noah, S. T.↗

Orbit transfer rocket engine integrated control and health monitoring system technology readiness assessment

The objectives of this task were to: (1) estimate the technology readiness of an integrated control and health monitoring (ICHM) system for the Aerojet 7500 lbF Orbit Transfer Vehicle engine preliminary design assuming space based operations; and (2) estimate the remaining cost to advance this technology to a NASA defined 'readiness level 6' by 1996 wherein the technology has been demonstrated with a system validation model in a simulated environment. The work was accomplished through the conduct of four subtasks. In subtask 1 the minimally required functions for the control and monitoring system was specified. The elements required to perform these functions were specified in Subtask 2. In Subtask 3, the technology readiness level of each element was assessed. Finally, in Subtask 4, the development cost and schedule requirements were estimated for bringing each element to 'readiness level 6'.

Bickford, R. L.↗

Application of enhanced modern structured analysis techniques to Space Station Freedom electric power system requirements

A team of Space Station Freedom (SSF) system engineers are in the process of extensive analysis of the SSF requirements, particularly those pertaining to the electrical power system (EPS). The objective of this analysis is the development of a comprehensive, computer-based requirements model, using an enhanced modern structured analysis methodology (EMSA). Such a model provides a detailed and consistent representation of the system's requirements. The process outlined in the EMSA methodology is unique in that it allows the graphical modeling of real-time system state transitions, as well as functional requirements and data relationships, to be implemented using modern computer-based tools. These tools permit flexible updating and continuous maintenance of the models. Initial findings resulting from the application of EMSA to the EPS have benefited the space station program by linking requirements to design, providing traceability of requirements, identifying discrepancies, and fostering an understanding of the EPS.

Biernacki, John↗

LVQ and backpropagation neural networks applied to NASA SSME data

Feedfoward neural networks with backpropagation learning have been used as function approximators for modeling the space shuttle main engine (SSME) sensor signals. The modeling of these sensor signals is aimed at the development of a sensor fault detection system that can be used during ground test firings. The generalization capability of a neural network based function approximator depends on the training vectors which in this application may be derived from a number of SSME ground test-firings. This yields a large number of training vectors. Large training sets can cause the time required to train the network to be very large. Also, the network may not be able to generalize for large training sets. To reduce the size of the training sets, the SSME test-firing data is reduced using the learning vector quantization (LVQ) based technique. Different compression ratios were used to obtain compressed data in training the neural network model. The performance of the neural model trained using reduced sets of training patterns is presented and compared with the performance of the model trained using complete data. The LVQ can also be used as a function approximator. The performance of the LVQ as a function approximator using reduced training sets is presented and compared with the performance of the backpropagation network.

Doniere, Timothy F.↗

Range Process Simulation Tool

Range Process Simulation Tool (RPST) is a computer program that assists managers in rapidly predicting and quantitatively assessing the operational effects of proposed technological additions to, and/or upgrades of, complex facilities and engineering systems such as the Eastern Test Range. Originally designed for application to space transportation systems, RPST is also suitable for assessing effects of proposed changes in industrial facilities and large organizations. RPST follows a model-based approach that includes finite-capacity schedule analysis and discrete-event process simulation. A component-based, scalable, open architecture makes RPST easily and rapidly tailorable for diverse applications. Specific RPST functions include: (1) definition of analysis objectives and performance metrics; (2) selection of process templates from a processtemplate library; (3) configuration of process models for detailed simulation and schedule analysis; (4) design of operations- analysis experiments; (5) schedule and simulation-based process analysis; and (6) optimization of performance by use of genetic algorithms and simulated annealing. The main benefits afforded by RPST are provision of information that can be used to reduce costs of operation and maintenance, and the capability for affordable, accurate, and reliable prediction and exploration of the consequences of many alternative proposed decisions.

Phillips, Dave↗

Bioreactor Development for CO2-Based In Situ Resource Utilization Manufacturing

Sustainable long-duration manned missions on both the Moon and Mars will require in situ resource utilization (ISRU). Carbon dioxide (CO2) has great potential as a harvestable resource, making up 95% of the atmosphere on Mars and being produced as respiratory waste in spacecraft and future planetary habitats. Through ISRU, biomanufacturing has the capability to produce a near limitless array of products from local space resources, which include pharmaceuticals, bioplastics, chemical feedstocks, and industrial enzymes. Here, a CO2-based ISRU recombinant protein bioreactor and associated biomanufacturing organisms were designed to produce a highly stable carbonic anhydrase (CA). Initial work characterized candidate organisms for growth on acetate and formic acid, carbon substrates that can be synthesized via electrochemical conversion of CO2. To improve growth on the CO2 producing substrate formic acid and for direct integration of ISRU CO2, a synthetic Calvin-Benson-Bassam cycle was designed for use in Cyberlindnera jadinii and Escherichia coli. Genetic modifications in E. coli will be facilitated by a tailored CRISPR/Cas9 and λ red recombineering two-vector system. For expression of CA, a blue light regulated T7 promoter was employed for dynamic and small molecule free induction. Efficient bioproduction through a fed-batch exponential feeding strategy was determined via mass balance calculations from ISRU substrates to biomass and CA yield. Flux balance analysis was used to model ISRU substrate metabolism and metabolic pathway engineering in candidate organisms under cultivation strategy conditions for both metabolism reconstruction and pathway design optimization. Finally, a small-scale, disposable bag bioreactor concept for use in the NASA Bioculture System infrastructure was designed to enable CO2-based CA production in reduced-gravity environments.

Biomanufacturing, Pathway Engineering, Flux Balanc↗

Durability and Design Issues of Thermal/environmental Barrier Coatings on Sic/sic Ceramic Matrix Composites Under 1650 C Test Conditions

Ceramic thermal/environmental barrier coatings for SiC-based ceramics will play an increasingly important role in future gas turbine engines because of their ability to effectively protect the engine components and further raise engine temperatures. However, the coating durability remains a major concern with the ever-increasing temperature requirements. Currently, advanced T/EBC systems, which typically include a high temperature capable zirconia- (or hahia-) based oxide top coat (thermal barrier) on a less temperature capable mullite/barium-strontium-aluminosilicate (BSAS)/Si inner coat (environmental barrier), are being developed and tested for higher temperature capability Sic combustor applications. In this paper, durability of several thermal/environmental barrier coating systems on SiC/SiC ceramic matrix composites was investigated under laser simulated engine thermal gradient cyclic, and 1650 C (3000 F) test conditions. The coating cracking and delamination processes were monitored and evaluated. The effects of temperature gradients and coating configurations on the ceramic coating crack initiation and propagation were analyzed using finite element analysis (FEA) models based on the observed failure mechanisms, in conjunction with mechanical testing results. The environmental effects on the coating durability will be discussed. The coating design approach will also be presented.

Zhu, Dong-Ming↗

Pilot-Scale Silicone Process for Low-Cost Carbon Dioxide Capture. Final Scientific/Technical Report

GE Global Research has developed, over the last 8 years, a platform of cost effective CO 2 capture technologies based on a non-aqueous aminosilicone solvent (GAP-1m). As demonstrated in a previous funded DOE project (DE-FE0007502), the GAP-1m solvent has increased CO 2 working capacity, lower volatility and corrosivity than the benchmark aqueous amine technology. The current report describes the cooperative program between GE Global Research (GE GRC), and the National Carbon Capture Center (NCCC) to design, construct, and operate a pilot-scale process using GAP-1m solvent to demonstrate its performance at 0.5 MWe. (i) Performance of the GAP-1m solvent was demonstrated in a 0.5 MWe pilot with real flue gas for over 900 hrs. of operation using two alternative desorption designs: a Continuous Stirred Tank Reactor (CSTR), and a Steam Stripper Column (SSC). The CSTR is a one-stage separation unit with reduced space requirements, and capital cost. The alternative is a multi-stage separation column, with improved desorption efficiency. Testing the two desorber options allowed us to identify the most cost effective, and space efficient desorber solution. (ii) CSTR Campaign: The CSTR desorber unit was designed, fabricated and integrated with the pilot solvent test unit (PSTU), replacing the PSTU Steam Stripper Column at NCCC. Solvent management and waste water special procedures were implemented to accommodate operation of the non-aqueous solvent in the PSTU. Performance of the GAP-1m solvent with the CSTR was demonstrated for over 500 hrs. while varying temperature of the desorption (230 – 265 oF), solvent circulation rate (GAP-1m : CO 2 (molar) = 1.5 – 4), and flue gas flow rates (0.2 – 0.5 MWe). Solvent carry-over in the CO 2 product was minimized by maintaining water content below 5 wt.%, and desorption pressure at 7 psig. CO 2 capture efficiency achieved was 95% at 0.25 MWe (GAP-1m : CO 2 = 4 (molar), 230 oF desorption), and 65% at 0.5 MWe (GAP-1m : CO 2 (molar) = 1.5, 248 oF). Solvent loss was dominated by thermal degradation of the rich solvent. (iii) Steam Stripper Column Campaign: Higher expected cost of the solvent vs. aqueous amines makes solvent management a top priority to maintain the low cost for the process. During the testing of the GAP-1m solvent with the CSTR, thermal degradation of the rich solvent was found to be the main mechanism in solvent loss. Small amounts of water in the working solution were found to be an effective way to enable steam stripping, thereby lowering desorption temperature, and hence reducing thermal degradation. Steam stripping also increased working capacity by 30% due to a more efficient desorption. The concept was first tested in a glass stripping column (lab scale, GE GRC), optimized in a continuous bench scale system (2 kWe, GE GRC), and demonstrated in a 0.5 MWe PSTU at NCCC. No special system modifications were required to the PSTU to accommodate the testing of the non-aqueous GAP-1 solvent with the regenerator column. SSC was found to be more robust towards solvent entrainment (H 2 O < 35 wt.%). 90 – 95% CO 2 capture efficiency was achieved under stoichiometric conditions at 0.5 MWe (235 oF desorption, 2 psig and 19 wt. % H 2 O). Both CO 2 capture efficiency and specific duty reached optimum conditions at 18 wt.% H 2 O. Low amine degradation (< 0.05 wt.%/day) was recorded over 350 hrs. of operation. Controlled water addition to GAP-1m solvent decreased the desorption temperature, thermal degradation, and improved the CO 2 working capacity due to more efficient absorption and desorption processes. Under these conditions, the GAP-1m solvent exhibited a 25% increased working capacity, and 10% reduction in specific steam duty vs. MEA, at 10 oF lower desorption temperature. (iv) Techno-economic Analysis: The pilot-scale PSTU engineering data were used to update the capture system process models, and the techno-economic analysis was performed for a 550 MW coal fired power plant. The 1st year CO 2 removal cost for the aminosilicone-based carbon-capture process was evaluated at $48/ton CO 2 using the steam stripper column. This is a 20% reduction compared to MEA, primarily due to lower overall capital cost. CO 2 cost using the CSTR desorber is dominated by the economics of the solvent make-up. The steam stripper desorber is the preferred unit operation due to a more efficient desorption, and reduced solvent make-up rate. Further reduction in CO 2 capture cost is expected by lowering the manufacturing cost of the solvent, implementing flowsheet optimization and/or implementing the next generation aminosilicone solvent with improved stability and increased CO 2 working capacity.

0.5 MW Pilot↗

Modeling supercritical CO 2 flow and mineralization in reactive host rocks with PFLOTRAN v7.0

Understanding the flow and reactivity of CO 2 injected into geological reservoirs is important for many subsurface applications including secure geologic carbon storage (GCS), critical mineral extraction, enhanced geothermal systems (EGS), and enhanced oil recovery (EOR). Traditionally, subsurface CO 2 injection for GCS applications has focused on geologic formations with favorable subsurface configurations for CO 2 migration and trapping through non-reactive mechanisms such as structural, solubility, and petrophysical trapping. Recently, CO 2 -reactive rocks such as mafic and ultramafic basalts have been investigated for their potential to react with injected CO 2 in situ to simultaneously dissolve host rock minerals and mineralize CO 2 as carbonates. Engineering rapid CO 2 mineralization in the subsurface is attractive because of the increased density of stored CO 2 , the additional safety factors associated with solidification, and the potential to extract valuable critical minerals. Here we present recent developments in the parallel flow and reactive transport simulator PFLOTRAN to model coupled CO 2 -brine flow and reactive transport for a wide range of injection and production applications involving reactive CO 2 -brine systems. These developments are based on the well established and trusted CO 2 flow capabilities in the STOMP-CO 2 simulator. New capabilities added to PFLOTRAN include new CO 2 -brine equations of state with optional thermal coupling, several new constitutive relationships like capillary pressure smoothing and scanning path hysteresis, a fully implicit well model, and native linkage with PFLOTRAN's well-established reactive transport libraries. A series of benchmarks between PFLOTRAN and STOMP-CO 2 verify the newly developed CO 2 -brine flow capabilities. Demonstrations of coupled CO 2 -brine flow modeling and reactive transport show how CO 2 mineralization can be engineered in reactive host rocks. Finally, an example use case involving copper leaching by CO 2 and critical mineral extraction is presented to showcase the strengths of this new implementation. Several limitations still remain, including limited availability of field data to parameterize models. Future work should constrain the evolution of mineral surface area during mineralization and the temperature and/or pH dependence of geochemical reactions for specific systems of interest.

Critical Minerals↗

Final Report for Project "A high-throughput pipeline for mapping inter-species interactions and metabolic synergy relevant to next-generation biofuel production"

The goal of our project was to implement a pipeline for the systematic, computationally-driven study and optimization of microbial interactions and their effect on lignocellulose degradation and biofuel production. We specifically sought to design and construct artificial microbial consortia that could collectively degrade lignocellulose from plant biomass, and produce precursors of energy-rich biofuels. This project fits into the bigger picture goal of helping identify a sustainable strategy for the production of energy-rich biofuels that would satisfy the existing energy constraints and demand of our society. Based on the observation that complex natural microbial communities tend to be metabolically efficient and ecologically robust, we pursued the study of a microbial system in which the desired engineering function is achieved through division of labor across multiple microbial species. Our approach was aimed at bypassing the complexity of natural communities by establishing a rational approach to design small synthetic microbial consortia. Towards this goal, we combined multiple approaches, including computer modeling of ecosystem-level microbial metabolism, mass spectrometry of metabolites, genetic engineering, and experimental evolution. The microbial production of biofuels from lignocellulose is a complex, multi-step process. Microbial consortia are an ideal approach to consolidated bioprocessing: a community of microorganisms performs a wide variety of functions more efficiently and is more resilient to environmental perturbations than a microbial monoculture. Each organism we chose for this project addresses a specific challenge: lignin degradation (Pseudomonas putida); (hemi)cellulose degradation (Cellulomonas fimi); lignin degradation product demethoxylation (Methylobacterium spp); generation of biofuel lipid precursors (Yarrowia lipolytica). These organisms are genetically tractable, aerobic, and have been used in biotechnological applications. Throughout the project, we have used mass spectrometry to characterize and measure the metabolic inputs and outputs of each of these consortium members, providing valuable information for model refinement, and enabling the establishment of metabolism-mediated interactions. In addition to lignocellulose degradation, we have started addressing the challenge of removing metabolites (e.g. formaldehyde) produced by the demethoxylation of lignin monomers, which can otherwise inhibit microbial growth due to their toxicity. On the computational side, we have implemented genome-scale models for all consortium members, based on KBase reconstructions and literature curation, and we studied small consortia and their properties. Overall, our project has identified a complex landscape of interactions types and metabolic processes relevant to community-level functions, illustrating the challenges and opportunities of microbial community engineering for the transformation of biomass into bioproducts.

59 BASIC BIOLOGICAL SCIENCES↗

Developing Deep Learning Models for System Remaining Useful Life Predictions: Application to Aircraft Engines

Prognostics and health management (PHM) is an important part of ensuring reliable operations of complex safety- critical systems. System-level remaining useful life (RUL) estimation is a much more complex problem than making estimations at the component level, and system-level RUL methodologies remain sparse in the literature. Model-based approaches have traditionally worked in the past for components such as capacitors, MOSFETs, batteries, or hard-drives (to name a few examples), but developing high fidelity dynamics models of cyber physical systems that can be used to study the effects of multiple degrading components in the system remains a challenging task. Some initial work on model-based System RUL predictions was demonstrated in Khorasgani, et al [1], but, to generalize the system-level prognostics problem, we have to resort to pure data driven and hybrid approaches. In this work, we propose an end-to-end data- driven framework for developing deep learning models to predict remaining useful life of cyber physical systems operating under unknown faulty conditions. The raw data is organized with a data schema that improves the model development process and down stream data analysis tasks. Due to the unknown faulty conditions, the raw sensor data is transformed into signals that expose the underlying degradation processes, which are then used for model development. Bayesian Optimization is used to tune the model parameters prior to training and validation. We show that this approach results in accurate predictions within 3 cycles to end of life (EOL). We demonstrate the effectiveness of our approach by applying it to the N-CMAPSS turbofan engine dataset recently released by NASA, which includes high fidelity degradation modeling, real world operating conditions, and a large set of fault operating modes.

Prognostics↗

Lunar surface vehicle model competition

During Fall and Winter quarters, Georgia Tech's School of Mechanical Engineering students designed machines and devices related to Lunar Base construction tasks. These include joint projects with Textile Engineering students. Topics studied included lunar environment simulator via drop tower technology, lunar rated fasteners, lunar habitat shelter, design of a lunar surface trenching machine, lunar support system, lunar worksite illumination (daytime), lunar regolith bagging system, sunlight diffusing tent for lunar worksite, service apparatus for lunar launch vehicles, lunar communication/power cables and teleoperated deployment machine, lunar regolith bag collection and emplacement device, soil stabilization mat for lunar launch/landing site, lunar rated fastening systems for robotic implementation, lunar surface cable/conduit and automated deployment system, lunar regolith bagging system, and lunar rated fasteners and fastening systems. A special topics team of five Spring quarter students designed and constructed a remotely controlled crane implement for the SKITTER model.

Source record↗

Update to the Performance Assessment for the Savannah River Site Saltstone Disposal Facility - 20124

In 2019, Savannah River Remediation developed a revision to the performance assessment (PA) on behalf of the U.S. Department of Energy (DOE) Savannah River Operations Office (SR) for the near-surface disposal of low-level waste at the Savannah River Site (SRS) Saltstone Disposal Facility (SDF). Soluble waste from SRS Tank Farms undergoes salt processing to remove cesium and other high activity constituents. The low-activity decontaminated salt solution (DSS) is then immobilized by mixing it into a cementitious waste form known as saltstone. After mixing, the saltstone is poured into leak-tight concrete vaults, known as saltstone disposal units (SDUs), where the waste form cures. By the time of facility closure, the SDF is expected to consist of 15 SDUs with a combined capacity of 1.06 E+09 L (280 Mgal) of cured saltstone. The facility operates under a Disposal Authorization Statement (DAS) from DOE and a permit from the South Carolina Department of Health and Environmental Control (SCDHEC). Since the start of operations in 1990, the SDF has received almost 6.7 E+07 L (18 Mgal) of DSS, resulting in the safe disposal of 2.7 E+16 Bq (7.3 E+05 Ci) of activity. Due to the radioactive decay of short-lived contaminants, the total remaining activity in the disposed waste is estimated to be approximately 1.4 E+16 Bq (3.9 E+05 Ci), as of September 2018. The Disposal Authorization Statement requires a demonstration that the system of engineered and natural features of the disposal facility will limit releases from the facility and be protective of human health and the environment for at least the next 1,000 years. The long-term performance of the facility was evaluated under the requirements of the DoE's Radioactive Waste Management Manual (US DOE Manual 435.1-1). Simulations were performed to demonstrate that the disposal facility would meet performance objectives specified in the manual. The evaluation was based on numerical models that simulate the releases of contaminants from the saltstone waste form. Contaminants were transported through groundwater and air pathways to points of assessment to evaluate compliance. In addition, the potential consequences of an inadvertent human intrusion (IHI) were also evaluated. In accordance with the guidance and recommendations in US DoE's technical standard for DAS, deterministic and probabilistic analyses were performed to demonstrate the SDF system, which includes the engineered cover system, the SDUs, the waste form, and the natural features of the site, provides a reasonable expectation that saltstone disposal will meet performance objectives. Post-closure doses to future members of the public (MOP) were evaluated; dose estimates from the air pathway were well below the 1.0 E-04 Sv/yr (10 mrem/yr) performance objective within 1,000 years, and the calculated doses to the MOP from all exposure pathways, including the groundwater and air pathways, were well below the 2.5 E-04 Sv/yr (25 mrem/yr) performance objective within 1,000 years. Doses following an assumed intrusion event within the facility boundaries were well below the IHI performance objectives, where the acute IHI dose was below the acute IHI dose performance objective of 5.0 E-03 Sv (500 mrem) and the chronic IHI dose was below the chronic IHI dose performance objective of 1.0 E-03 Sv/yr (100 mrem/yr) within 1,000 years. (author)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Asymptotic analysis of the fluid flow with a pressure-dependent viscosity in a system of thin pipes

We consider the incompressible fluid with a pressure-dependent viscosity flowing through a multiple pipe system. The viscosity–pressure relation is given by the Barus law commonly used in the engineering applications. Assuming that the ratio between pipes thickness and its length is small, we propose a rigorous asymptotic approach based on the concept of the transformed pressure. As a result, we obtain new macroscopic model describing the effective behavior of the fluid in the system. In particular, the generalized version of the Kirchhoff’s law is derived giving the explicit formula for the junction pressure. The error estimate for the asymptotic approximation is also provided. Mathematical analysis presented here can be applied to a general viscosity–pressure relation satisfied by other empiric laws.

97 MATHEMATICS AND COMPUTING↗

Assessments of Hollow Cathode Wear in the Xenon Ion Propulsion System (XIPs(c)) by Numerical Analyses and Wear Tests

The standard approach presently followed by NASA to qualify electric propulsion for the required mission throughput has been based largely on life tests, which can be costly and time consuming. Revised electric propulsion lifequalification approaches are being formulated that combine analytical and/or computational methods with (shorter-duration) wear tests. As a model case, a wear test is being performed at JPL to assess the lifetime of the discharge hollow cathode in the Xenon Ion Propulsion System (XIPS(c)), a 25-cm ion engine developed by L-3 Communications Electron Technologies, Inc. for commercial applications. Wear and plasma data accumulated throughout this life-assessment program are being used to validate the existing 2-D hollow cathode code OrCa2D. We find that the OrCa2D steady-state solution predicts very well the time-averaged plasma data and the keeper voltage after 5500 hrs of operation in high-power mode. When the wave motion that occurs naturally in these devices is accounted for, based on an estimate of the maximum wave amplitude, the molybdenum-keeper erosion profile observed in the XIPS(c) discharge cathode is also reproduced within a factor of two of the observation. When the same model is applied to predict the erosion of a tantalum keeper we find that erosion is reduced by more than two orders of magnitude compared to the molybdenum keeper due the significantly lower sputtering yield of tantalum. A tantalum keeper would therefore allow keeper lifetimes that greatly exceed the present requirements for deep-space robotic missions considered by NASA. Moreover, such large reduction of the erosion renders the largest uncertainties in the models, which are associated with the wave amplitude estimates and the electron transport model, negligible.

plasma simulations↗

Knowledge-matching based computational framework for genome-scale metabolic model refinement

Genome-scale metabolic models (GEMs) are mathematically structured knowledge base reconstructed from annotated genome of different organisms. With the advancement of next-generation sequencing technology, many organisms have had their genomes sequenced. However, obtaining a high-quality GEM is highly time-consuming, even with the introduction of several genome-scale reconstruction tools that offer automated draft network generation and gap filling. It has been recognized that the iterative process of manual curation and refinement is the limiting step of GEM development, and how to expedite the GEM refinement is still an open question. As cellular metabolism is a complex system with very high degree of freedom and redundancy, the principles and techniques developed in process systems engineering can be adapted to expedite GEM refinement. In this paper we present a knowledge-matching based computation framework for GEM refinement, and demonstrate the effectiveness of the proposed solution using the refinement of a GEM for Clostridium tyrobutyricum.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗