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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Neural networks for modeling and control of particle accelerators

Charged particle accelerators support a wide variety of scientific, industrial, and medical applications. They range in scale and complexity from systems with just a few components for beam acceleration and manipulation, to large scientific user facilities that span many kilometers and have hundreds-to-thousands of individually-controllable components. Specific operational requirements must be met by adjusting the many controllable variables of the accelerator. Meeting these requirements can be challenging, both in terms of the ability to achieve specific beam quality metrics in a reliable fashion and in terms of the time needed to set up and maintain the optimal operating conditions. One avenue toward addressing this challenge is to incorporate techniques from the fields of machine learning (ML) and artificial intelligence (AI) into the way particle accelerators are modeled and controlled. While many promising approaches within AI/ML could be used for particle accelerators, this dissertation focuses on approaches based on neural networks. Neural networks are particularly well-suited to modeling, control, and diagnostic analysis of nonlinear systems, as well as systems with large parameter spaces. They are also very appealing for their ability to process high-dimensional data types, such as images and time series (both of which are ubiquitous in particle accelerators). In this work, key studies that demonstrated the potential utility of modern neural network-based approaches to modeling and control of particle accelerators are presented. The context for this work is important: at the start of this work in 2012, there was little interest in AI/ML in the particle accelerator community, and many of the advances in neural networks and deep learning that enabled its present success had not yet been made at that time. As such, this work was both an exploration of possible application areas and a generator of proof-of-concept demonstrations in these areas.

43 PARTICLE ACCELERATORS↗
DOE OSTI2017

Method for Hot Real-Time Sampling of Pyrolysis Vapors

Biomass Pyrolysis has been an increasing topic of research, in particular as a replacement for crude oil. This process utilizes moderate temperatures to thermally deconstruct the biomass which is then condensed into a mixture of liquid oxygenates to be used as fuel precursors. Pyrolysis oils contain more than 400 compounds, up to 60 percent of which do not re-volatilize for subsequent chemical analysis. Vapor chemical composition is also complicated as additional condensation reactions occur during the condensation and collection of the product. Due to the complexity of the pyrolysis oil, and a desire to catalytically upgrade the vapor composition before condensation, online real-time analytical techniques such as Molecular Beam Mass Spectrometry (MBMS) are of great use. However, in order to properly sample hot pyrolysis vapors, many challenges must be overcome. Sampling must occur within a narrow range of temperatures to reduce product composition changes from overheating or partial condensation or plugging of lines from condensed products. Residence times must be kept at a minimum to reduce further reaction chemistries. Pyrolysis vapors also form aerosols that are carried far downstream and can pass through filters resulting in build-up in downstream locations. The co-produced bio-char and ash from the pyrolysis process can lead to plugging of the sample lines, and must be filtered out at temperature, even with the use of cyclonic separators. A practical approach for considerations and sampling system design, as well as lessons learned are integrated into the hot analytical sampling system of the National Renewable Energy Laboratory's (NREL) Thermochemical Process Development Unit (TCPDU) to provide industrially relevant demonstrations of thermochemical transformations of biomass feedstocks at the pilot scale.

09 BIOMASS FUELS↗
DOE OSTI2015

The development and initial testing of the Ice Pig cleaning method for nuclear reprocessing plants - 15363

There are numerous situations throughout the nuclear industry where it would be advantageous to clean out enclosed systems, e.g. ducts and pipes, to remove sediments and radioactive contamination. However, conventional flushing methods result in the production of significant volumes of contaminated liquor. The wall Shear achieved with water flushing is insufficient to remove and carry dense deposits often found in nuclear facilities. Conventional mechanical pigs can be propelled through the duct by application of a driving medium such as compressed air or water. These are able to achieve very high wall shears, but can also get physically stuck where there is variation in the pipe / duct diameter or small radius bends. The field of application is best suited to straight constant diameter systems with no discontinuities such as Tee pieces, valves and in-pipe instrumentation. Driven by the desire to clean and displace radioactive materials from complex topology ducts and pipes, without the risk of having conventional pigs becoming lodged in a plant and coupled with the need to minimize effluent volumes, the UK Nuclear Industry led by Sellafield Limited (on behalf of the UK Nuclear Decommissioning Authority), has worked to demonstrate and underpin the use of the ice pigging technology for the nuclear industry. It is found that high ice fraction slurries flow as viscous liquids that exhibit a number of mechanical properties that offer much higher shear rates. The 'Ice Pig' exerts shear rates on pipe walls which are typically 1000 times greater than those achieved with water flowing at the same velocity. The 'Ice Pig' is able to negotiate almost any topology, flow through pipe networks of vastly differing diameter, through heat exchangers and in-line instrumentation etc. Experimental data and operational experience from other industries demonstrates that whilst there is high shear, the 'Ice Pig' does not damage the surface of the pipe wall. A further attractive characteristic of the 'Ice Pig' is that it eventually melts rendering it a simple effluent for processing by downstream processes. Due to the special nature of ice slurry, its unique rheological and physical characteristics, together with the complementary underpinning experimental work undertaken by Sellafield Limited enables the Ice Pigging process to move from an 'interesting' technology to one suitable for use by the nuclear industry for operations, Post Operational Clean Out (POCO) and decommissioning. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1994

Communication Research in Aviation and Space Operations: Symptoms and Strategies of Crew Coordination

The day-to-day operators of today's aerospace systems work under increasing pressures to accomplish more with less. They work in operational systems which are complex, technology-based, and high-risk; in which incidents and accidents have far-reaching and costly consequences. For these and other reasons, there is concern that the safety net formerly built upon redundant systems and abundant resources may become overburdened. Although we know that human ingenuity can overcome incredible odds, human nature can also fail in unpredictable ways. Over the last 20 years, a large percentage of aviation accidents and incidents have been attributed to human errors rather than hardware or environmental factors alone. A class of errors have been identified which are not due to a lack of individual, technical competencies. Rather, they are due to the failure of teams to utilize readily available resources or information in a timely fashion. These insights began a training revolution in the aviation industry called Cockpit Resource Management, which later became known as Crew Resource Management (CRM) as its concepts and applications extended to teams beyond the flightdeck. Then, as now, communication has been a cornerstone in CRM training since crew coordination and resource management largely resides within information transfer processes--both within flightcrews, and between flightcrews and the ground operations teams that support them. The research I will describe takes its roots in CRM history as we began to study communication processes in order to discover symptoms of crew coordination problems, as well as strategies of effective crew management. On the one hand, communication is often the means or the tool by which team members manage their resources, solve problems, maintain situational awareness and procedural discipline. Conversely, it is the lack of planning and resource management, loss of vigilance and situational awareness, and non-standard communications that are implicated in accidents and incidents. NASA/Ames Crew Factors researchers have been developing a model of effective crew coordination in order to understand the sources of performance breakdowns, and to develop effective solutions and interventions. Because communication is a primary mechanism by which information is received and transmitted, and because it is observable behavior, we focus on these group processes in order to identify patterns of communication that distinguish effective from less effective crew performance. Since a prime objective is to develop training recommendations for enhancing communication skills, we interpret our findings in the context of relevant task and environmental conditions, role and procedural constraints, and the normal real-time parameters of flight operations. Another research objective is to consider how communication and coordination can be enhanced through design. For example, flight deck and hardware design as well as procedural and software design may greatly influence the efficiency with which crews communicate and coordinate their work. In addition, teams and tasks may be designed, organized, and trained so that team interactions with each other are based upon appropriately shared knowledge, procedures and situation awareness. In short, we are interested in enhancing communication practices through (1) the training of specific communication skills, and (2) the design of equipment, tasks, procedures, and teams that optimize smooth, unambiguous communication processes. Two examples of communication research will be described; one in aviation and one in space operations. The first example is a high-fidelity full mission simulation study which investigates the affect of flightdeck automation on crew coordination and communication (contrasting crew performance in the DC-9 vs. MD88). Additional information is contained in the original extended abstract.

Kanki, Barbara G.↗
DOE OSTI2023

Commercial, industrial, and institutional discount rate estimation for efficiency standards analysis: Sector-level data 1998–2022

Underlying each of the U.S. Department of Energy’s (DOE’s) federal appliance and equipment energy conservation standards are a set of complex analyses of the projected costs and benefits of regulation. Any new or amended standard must be designed to achieve significant additional energy conservation, provided that it is technologically feasible and economically justified (42 U.S.C. 6295(o)(2)(A)). DOE determines economic justification based on whether the benefits exceed the burdens, considering a variety of factors, including the economic impact of the standard on consumers of the product and the savings in lifetime operating cost compared to any increase in price or maintenance expenses (42 U.S.C. 6295(o)(2)(B)). As part of this determination, DOE conducts a life-cycle cost (LCC) analysis, which models the combined impact of appliance first cost and operating cost changes on a representative commercial building sample to identify the fraction of customers achieving LCC savings or incurring net cost at the considered efficiency levels. Thus, the commercial discount rate value(s) used to calculate the present value of energy cost savings within the LCC model implicitly plays a role in estimating the economic impact of potential standard levels. This report provides an in-depth discussion of the commercial discount rate estimation process. It is an update to previous reports on estimating commercial discount rates from firm-level and sector-level financial data (e.g., Fujita, 2021, 2016). Major topics covered in this report include the following: -Discount rate estimation methods and rationale -Data sources used and data limitations -Discount rate distributions for use in standards analysis -Discount rate estimation methods and distributions specific to the small business subgroup analysis A version of this analysis was most recently released in 2022. Going forward, this report will be updated as data allow and analyses necessitate.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Commercial, industrial, and institutional discount rate estimation for efficiency standards analysis: Sector-level data 1998–2023

Underlying each of the U.S. Department of Energy’s (DOE’s) federal appliance and equipment energy conservation standards are a set of complex analyses of the projected costs and benefits of regulation. Any new or amended standard must be designed to achieve significant additional energy conservation, provided that it is technologically feasible and economically justified (42 U.S.C. 6295(o)(2)(A)). DOE determines economic justification based on whether the benefits exceed the burdens, considering a variety of factors, including the economic impact of the standard on consumers of the product and the savings in lifetime operating cost compared to any increase in price or maintenance expenses (42 U.S.C. 6295(o)(2)(B)). As part of this determination, DOE conducts a life-cycle cost (LCC) analysis, which models the combined impact of appliance first cost and operating cost changes on a representative commercial building sample to identify the fraction of customers achieving LCC savings or incurring net cost at the considered efficiency levels. Thus, the commercial discount rate value(s) used to calculate the present value of energy cost savings within the LCC model implicitly plays a role in estimating the economic impact of potential standard levels. This report provides an in-depth discussion of the commercial discount rate estimation process relying on the Capital Asset Pricing Model (CAPM) to estimate a business’ cost of equity, and by adding a risk adjustment factor to the risk-free rate associated with long-term U.S. Treasury bonds to estimate their cost of debt. It is an update to previous reports on estimating commercial discount rates from firm-level and sector-level financial data (e.g., Fujita, 2021, 2016). Major topics covered in this report include the following: • Discount rate estimation methods and rationale • Data sources used and data limitations • Discount rate distributions for use in standards analysis • Discount rate estimation methods and distributions specific to the small business subgroup analysis.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Additively Manufactured Single-Use Molds and Reusable Patterns for Large Automotive and Hydroelectric Components

Additive manufacturing (AM) has the potential to reduce costs in the casting industry, particularly for large parts (i.e., components with any dimension > 12 in.). In this study, pilot-scale production case studies of hydroelectric and automotive parts were used to evaluate two AM-enabled casting methods: the direct printing of sand molds by binder jet and printing of reusable cope and drag patterns for sand casting. An additional benefit was found when additively manufactured patterns were used in combination with heat-treat free aluminum alloys, to produce castings of complex hydrodynamic surfaces. These parts previously required production via subtractive machining due to part distortion induced by the quench step of heat treatments. The machine types used for the three case studies are sand-binder jet, high-resolution polymer fused deposition modeling (FDM), and big area additive manufacturing (BAAM) FDM in combination with CNC machining. Each method demonstrated distinct advantages over traditional casting practices in particular use cases. Single-use molds show great reductions in start-up cost to produce one-off or legacy parts, and additively manufactured impression patterns show promise for innovating the tooling design process for complex geometry and large castings.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Design Concepts for an Outage Control Center Information Dashboard

The nuclear industry, and the business world in general, is facing a rapidly increasing amount of data to be dealt with on a daily basis. In the last two decades, the steady improvement of data storage devices and means to create and collect data along the way influenced the manner in which we deal with information. Most data is still stored without filtering and refinement for later use. Many functions at a nuclear power plant generate vast amounts of data, with scheduled and unscheduled outages being a prime example of a source of some of the most complex data sets at the plant. To make matters worse, modern information and communications technology is making it possible to collect and store data faster than our ability to use it for making decisions. However, in most applications, especially outages, raw data has no value in itself; instead, managers, engineers and other specialists want to extract the information contained in it. The complexity and sheer volume of data could lead to information overload, resulting in getting lost in data that may be irrelevant to the task at hand, processed in an inappropriate way, or presented in an ineffective way. To prevent information overload, many data sources are ignored so production opportunities are lost because utilities lack the ability to deal with the enormous data volumes properly. Decision-makers are often confronted with large amounts of disparate, conflicting and dynamic information, which are available from multiple heterogeneous sources. Information and communication technologies alone will not solve this problem. Utilities need effective methods to exploit and use the hidden opportunities and knowledge residing in unexplored data resources. Superior performance before, during and after outages depends upon the right information being available at the right time to the right people. Acquisition of raw data is the easy part; instead, it is the ability to use advanced analytical, data processing and data visualization methods to turn the data into reliable information and comprehensible, actionable information. Techniques like data mining, filtering and analysis only work reliably for well-defined and well-understood problems. The path from data to decision is more complex. The ability to communicate knowledge during outages and emergent issues is crucial. This paper presents an approach to turn the unused data into an opportunity: applying principles from semiotics, human factors and visual analytics to transform the traditional way of processing outage data into media that will improve the collective situation awareness, knowledge, decisions, actions and overall performance of the entire outage team, and also support the reliability, quality and overall effectiveness of maintenance work. The application of the proposed visualization methods will become the medium of a semi-automated analytical process where humans and machines cooperate using their respective, distinct capabilities for the most effective results.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Biochemical Process Modeling and Simulation (BPMS)

The Biochemical Process Modeling and Simulation project aims to reduce the cost and time of research by applying theory, modeling, and simulation to the most relevant bottlenecks in the biochemical process. We use molecular modeling, quantum mechanics, metabolic modeling, fluid dynamics, and reaction-diffusion methods in close collaboration with pretreatment, hydrolysis, upgrading, and TEA. The project's outcomes are increased yields and efficiency of the biochemical process, added value to products, and reduced price of fuels by specifically targeting catalytic efficiency, reactor design, enzyme efficiency, and microbial design. We work closely with experimental projects to identify problems and iterate with experiments to find and refine solutions. By working with experimentalists, we decide on problems that can be solved with simulation that could otherwise not be solved or would take too long with experiment alone to reach BETO's targets. Over the years, we have produced solutions that have resulted in determining the most likely fatty-acid derivative for passive transport out of bacteria that upgrade biomass, and we have also designed enzyme mutations for enhanced lignin upgrading. Metabolic models have been developed to tune the activity of 2,3 butanediol production for the 2030 target. A computational method to deliver understanding of how complex omics data can be interpreted in the metabolic pathways of organisms used in the Agile Biofoundry. We have found methods to overcome specific barriers and continue to develop those methods. Our reactor studies have guided the design of both the microbes and reactors for aerobic and micro-aerobic production at all scales and have been instrumental in improving the accuracy of techno-economic analysis models. This project is essential in the process of selecting the final processes for 2030 SAF production targets. More specifically, recently, we have: 1) Predicted the strength of the basic structural interactions in commodity plastics to provide guidance for plastics upcycling strategies. 2) Developed computational tool to improve the characterization of lignin-derived compounds 3) Developed new methodologies to enable Machine Learning-based Directed Evolution for protein engineering. 4) Developed Machine Learning methods to predict protein promiscuity and mutations to further improve microbial and enzymatic driven processes and demonstrated the utility of ML approaches to engineering proteins from sparse experimental datasets. 5) Developed new methods to enable high-fidelity simulation of aerobic fermentation at industrial scale and resolving mismatch of time scales through subcycling/operator splitting 7) Identified the difficulty in preventing local high-oxygen conditions in industrial bubble columns, which leads to less-desirable acetoin production, suggesting future research directions in alternative reactor configurations (e.g loop reactors, shallow-channel reactors).

BIOMASS FUELS↗
DOE OSTI2022

Commercial, industrial, and institutional discount rate estimation for efficiency standards analysis: Sector-level data 1998–2021

Underlying each of the Department of Energy’s (DOE’s) federal appliance and equipment energy conservation standards are a set of complex analyses of the projected costs and benefits of regulation. Any new or amended standard must be designed to achieve significant additional energy conservation, provided that it is technologically feasible and economically justified (42 U.S.C. 6295(o)(2)(A)). DOE determines economic justification based on whether the benefits exceed the burdens, considering a variety of factors, including the economic impact of the standard on consumers of the product and the savings in lifetime operating cost compared to any increase in price or maintenance expenses (42 U.S.C. 6295(o)(2)(B)). As part of this determination, DOE conducts a Life-Cycle Cost (LCC) analysis, which models the combined impact of appliance first cost and operating cost changes on a representative commercial building sample in order to identify the fraction of customers achieving LCC savings or incurring net cost at the considered efficiency levels. Thus, the commercial discount rate value(s) used to calculate the present value of energy cost savings within the LCC model implicitly plays a role in estimating the economic impact of potential standard levels. This report provides an in-depth discussion of the commercial discount rate estimation process. It is an update to previous reports on estimating commercial discount rates from firm-level financial data (Fujita, 2016). Major topics covered in this report include: Discount rate estimation methods and rationale; -Data sources used and data limitations; -Discount rate distributions for use in standards analysis; -Discount rate estimation methods and distributions specific to the small business subgroup analysis. Going forward, this report will be updated as data allow and analyses necessitate.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Evolution Mechanism of Oxide Inclusions in Titanium-Stabilized AISI 443 Stainless Steel

The evolution mechanism of oxide inclusions in Ti-bearing AISI 443 stainless steel was investigated by industrial experiment and thermodynamic calculation. The chemical compositions of steel and the characteristics of inclusions in steel were analyzed. After the addition of Al, the main type of inclusions in molten steel was irregular MgO·Al{sub 2}O{sub 3} spinel. The MgO·Al{sub 2}O{sub 3} inclusions were modified to be spherical CaO-Al{sub 2}O{sub 3}-MgO inclusions after calcium treatment. Thermodynamic calculation results indicated that several ppm Ca could significantly expand the liquid oxide phase field and decrease the stability of spinel. After titanium addition, two types of inclusions were formed: spherical Al{sub 2}O{sub 3}-TiO{sub x} inclusions and complex CaO-TiO{sub x}-Al{sub 2}O{sub 3}-MgO inclusions. The compositions of steel after Ti addition were mostly located in Al{sub 2}O{sub 3}-TiO{sub x} stability phase field. Based on the characteristics of inclusions in steel and thermodynamic calculation, inclusions consisting of liquid and CaTiO{sub 3} were formed in molten steel with more than 10 ppm Ca during the Ti addition process. The evolution mechanism of oxide inclusions was discussed with the consideration of the initial calcium content before Ti addition.

36 MATERIALS SCIENCE↗
NASA NTRS1994

Brush seal numerical simulation: Concepts and advances

The development of the brush seal is considered to be most promising among the advanced type seals that are presently in use in the high speed turbomachinery. The brush is usually mounted on the stationary portions of the engine and has direct contact with the rotating element, in the process of limiting the 'unwanted' leakage flows between stages, or various engine cavities. This type of sealing technology is providing high (in comparison with conventional seals) pressure drops due mainly to the high packing density (around 100 bristles/sq mm), and brush compliance with the rotor motions. In the design of modern aerospace turbomachinery leakage flows between the stages must be minimal, thus contributing to the higher efficiency of the engine. Use of the brush seal instead of the labyrinth seal reduces the leakage flow by one order of magnitude. Brush seals also have been found to enhance dynamic performance, cost less, and are lighter than labyrinth seals. Even though industrial brush seals have been successfully developed through extensive experimentation, there is no comprehensive numerical methodology for the design or prediction of their performance. The existing analytical/numerical approaches are based on bulk flow models and do not allow the investigation of the effects of brush morphology (bristle arrangement), or brushes arrangement (number of brushes, spacing between them), on the pressure drops and flow leakage. An increase in the brush seal efficiency is clearly a complex problem that is closely related to the brush geometry and arrangement, and can be solved most likely only by means of a numerically distributed model.

Braun, M. J.↗
DOE OSTI2021

Toward Automated Sampling of Polymorph Nucleation and Free Energies with the SGOOP and Metadynamics

Understanding the driving forces behind the nucleation of different polymorphs is of great importance for material sciences and the pharmaceutical industry. This includes understanding the reaction coordinate that governs the nucleation process and correctly calculating the relative free energies of different polymorphs. Here, we demonstrate, for the prototypical case of urea nucleation from the melt, how one can learn such a one-dimensional reaction coordinate as a function of prespecified order parameters and use it to perform efficient biased all-atom molecular dynamics simulations. The reaction coordinate is learnt as a function of the generic thermodynamic and structural order parameters using the “spectral gap optimization of order parameters (SGOOP)” approach [Tiwary, P. and Berne, B. J. Proc. Natl. Acad. Sci. U.S.A. (2016)] and is biased using well-tempered metadynamics simulations. The reaction coordinate gives insights into the role played by different structural and thermodynamics order parameters, and the biased simulations obtain accurate relative free energies for different polymorphs. This includes an accurate prediction of the approximate pressure at which urea undergoes a phase transition and one of the metastable polymorphs becomes the most stable conformation. Here, we believe the ideas demonstrated in this work will facilitate efficient sampling of nucleation in complex, generic systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Surveying Phase Modifier Functional Groups for Applications to Ln(III) Separations

The application of N,N,N',N'-tetraoctyl diglycolamide (TODGA) in solvent extraction systems for lanthanide (Ln) separations is well understood. In these systems, the formation of a third phase has motivated the use of phase modifiers to enable higher concentrations of H + and Ln common to industrial processes. Several different phase modifiers with applications to diglycolamide (DGA) systems have previously been reported, with a focus on tri-n-butyl phosphate (TBP), N,N'-dihexylactanamide (DHOA), N,N-dioctyl-2-hydroxyacetamide (DOHyA), N,N'-dimethyl-N,N'-dioctylhexylethoxy malonamide (DMDOHEMA), and octanol. While the primary utility of phase modifiers is the increased metal loading, they can have significant effects on the metal distribution ratios, which are well described by the energetics of the extraction process itself. However, the mechanisms by which phase modifiers impact distribution ratios are not generally understood. This work considers the ability of phase modifiers to affect Ln distribution ratios by using phase modifiers with two different functional groups (–Cl and –C≡N) and an octyl alkyl chain in a TODGA and n-dodecane system. Determining the effect of chlorooctane and octane nitrile is important for understanding how phase modifier functional groups and their hydrogen bonding interactions affect Ln extraction. Through combining distribution ratio measurements with organic phase spectroscopic investigations, the impact of chlorooctane and octane nitrile on Ln extraction and their inner-sphere complexes is reported. The addition of either chlorooctane or octane nitrile to TODGA in n-dodecane decreases Ln extraction while maintaining the same inner-sphere Ln complex. The lack of change in inner-sphere Ln-TODGA coordination upon incorporation of phase modifiers and the significant impact of these phase modifiers on distribution ratios suggest the importance of a supramolecular structure. Understanding the role of chlorooctane and octane nitrile on the organic phase structure at longer length scales has been identified as an avenue for future investigations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Self-Assembling Cell-Free Systems for Scalable Bioconversion

This project focused on developing cell-free systems to directly express multi-enzyme catalysts and perform CO2 bioconversions for industrial chemical production. The use of cell-free expression (CFE) systems derived from bacterial lysates is emerging as a promising approach for biomanufacturing. CFEs are genetically programmable, permit the expression of toxic enzymes, and allow for rapid prototyping of metabolic pathways. Research Contributions: 1. Understanding the Area Investigated: This research advances the understanding of cell-free systems by demonstrating their capability to perform complex multi-enzyme reactions. By directly expressing multi-gene systems, CFEs avoid the high costs and inefficiencies associated with producing and purifying enzymes for multi-step pathways. 2. Technical Effectiveness and Economic Feasibility: The project successfully engineered a CFE-based multienzyme biocatalyst for the de novo synthesis of serine and glycine from CO2 equivalents (formate and bicarbonate) and ammonia. This method achieved a 30% conversion rate of formate into these industrially important amino acids. Additionally, an 8-gene CFE biocatalyst was developed to produce malate, conserving 43% of carbon that would otherwise be lost as CO2. This approach has the potential to reach higher carbon efficiency than microbial production. 3. Public Benefit: The cell-free production of chemicals like serine, glycine, and malate using electrochemically generated formate could significantly reduce CO2 emissions. For example, satisfying the global malate market with this method could avoid approximately 400,000 tons of CO2 emissions annually. This work demonstrates the potential of CFE systems to produce platform chemicals, contributing to environmental sustainability and reducing reliance on petrochemicals. Future Prospects: The CFE-based biocatalyst process could be extended to produce a variety of chemicals, including other industrial di-acids, aromatics, terpenes, alcohols, and polymers. This project showcases the capabilities of cell-free expression systems for prototyping carbon-conserving pathways and sustainably bioproducing platform chemicals, marking a significant step towards economically-viable industrial processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

LaserSnake2: Remote High Powered Laser Cutting in Confined Hazardous Spaces - 16161

LaserSnake2, a UK collaborative project, seeks to deliver remotely operated cutting techniques into high hazard nuclear environments. This paper describes the developments and results of combining proven robotic manipulators with high-powered laser cutting tools, to allow for selective dismantling within complex nuclear process cells. Decommissioning old and poorly catalogued nuclear plant is a problem faced the world over. Designed with little consideration for decommissioning, or adapted significantly from the original drawings, legacy plant and infrastructure is full of spaces where it is undesirable or impossible to send people. Typically, a process cell or cave will require modification to ensure suitability for human entry or deployment of heavy duty equipment to complete the decontamination processes. The process of widening access routes, or selectively moving sections of highly contaminated material, is ideally suited to remote handling technology. The results of TWI's research into fibre-delivered laser cutting techniques, and integration with a dexterous snake-arm robot, are presented. Coupled with novel laser process head design and diffractive optical elements, the result is an integrated system capable of cutting up to 100 mm thick C-Mn steel plate at significant stand-off distances, encompassing the range of infrastructure found in a typical nuclear plant. Two options have been considered for deployment of the laser cutting tool. The first is focused on a fixed installation using a standard industrial robot. The second is a large, highly flexible snake-arm robot capable of entering cluttered cells through existing penetrations. Designed to operate through a standard 11'' MSM port, the 4.5 m snake-arm robot has the capacity to carry grippers, sensors or the laser cutting tool at the tip. The snake-arm is sealed and housed within a glove box for contamination control, allowing operation within a radioactive environment. Significant technical developments and material research are presented which have led to improved operational life, payload and bend. This paper describes the series of inactive trials which have been conducted to demonstrate the LaserSnake2 system's capabilities. These include: horizontal and vertical deployment, underwater operation, object manipulation and laser cutting. With global nuclear decommissioning costs running in to the $trillions, safe and cost efficient tools such as the LaserSnake2 system are essential as part of the decommissioning toolbox. Remote handling can account for up to 20% of a decommissioning project's costs, however significant time and financial savings can be made by utilising this new technology to reduce operator exposure and reach previously inaccessible areas. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1997

Enhanced Multiobjective Optimization Technique for Comprehensive Aerospace Design

A multidisciplinary design optimization procedure which couples formal multiobjectives based techniques and complex analysis procedures (such as computational fluid dynamics (CFD) codes) developed. The procedure has been demonstrated on a specific high speed flow application involving aerodynamics and acoustics (sonic boom minimization). In order to account for multiple design objectives arising from complex performance requirements, multiobjective formulation techniques are used to formulate the optimization problem. Techniques to enhance the existing Kreisselmeier-Steinhauser (K-S) function multiobjective formulation approach have been developed. The K-S function procedure used in the proposed work transforms a constrained multiple objective functions problem into an unconstrained problem which then is solved using the Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm. Weight factors are introduced during the transformation process to each objective function. This enhanced procedure will provide the designer the capability to emphasize specific design objectives during the optimization process. The demonstration of the procedure utilizes a computational Fluid dynamics (CFD) code which solves the three-dimensional parabolized Navier-Stokes (PNS) equations for the flow field along with an appropriate sonic boom evaluation procedure thus introducing both aerodynamic performance as well as sonic boom as the design objectives to be optimized simultaneously. Sensitivity analysis is performed using a discrete differentiation approach. An approximation technique has been used within the optimizer to improve the overall computational efficiency of the procedure in order to make it suitable for design applications in an industrial setting.

Chattopadhyay, Aditi↗