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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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At least 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Refactoring the Genetic Code for Increased Evolvability

ABSTRACT The standard genetic code is robust to mutations during transcription and translation. Point mutations are likely to be synonymous or to preserve the chemical properties of the original amino acid. Saturation mutagenesis experiments suggest that in some cases the best-performing mutant requires replacement of more than a single nucleotide within a codon. These replacements are essentially inaccessible to common error-based laboratory engineering techniques that alter a single nucleotide per mutation event, due to the extreme rarity of adjacent mutations. In this theoretical study, we suggest a radical reordering of the genetic code that maximizes the mutagenic potential of single nucleotide replacements. We explore several possible genetic codes that allow a greater degree of accessibility to the mutational landscape and may result in a hyperevolvable organism that could serve as an ideal platform for directed evolution experiments. We then conclude by evaluating the challenges of constructing such recoded organisms and their potential applications within the field of synthetic biology. IMPORTANCE The conservative nature of the genetic code prevents bioengineers from efficiently accessing the full mutational landscape of a gene via common error-prone methods. Here, we present two computational approaches to generate alternative genetic codes with increased accessibility. These new codes allow mutational transitions to a larger pool of amino acids and with a greater extent of chemical differences, based on a single nucleotide replacement within the codon, thus increasing evolvability both at the single-gene and at the genome levels. Given the widespread use of these techniques for strain and protein improvement, along with more fundamental evolutionary biology questions, the use of recoded organisms that maximize evolvability should significantly improve the efficiency of directed evolution, library generation, and fitness maximization.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Distinct Physiological Roles of the Three Ferredoxins Encoded in the Hyperthermophilic Archaeon Thermococcus kodakarensis

Control of electron flux is critical in both natural and bioengineered systems to maximize energy gains. Both small molecules and proteins shuttle high-energy, low-potential electrons liberated during catabolism through diverse metabolic landscapes. Ferredoxin (Fd) proteins—an abundant class of Fe-S-containing small proteins—are essential in many species for energy conservation and ATP production strategies. It remains difficult to model electron flow through complicated metabolisms and in systems in which multiple Fd proteins are present. The overlap of activity and/or limitations of electron flux through each Fd can limit physiology and metabolic engineering strategies. Here we establish the interplay, reactivity, and physiological role(s) of the three ferredoxin proteins in the model hyperthermophile Thermococcus kodakarensis . We demonstrate that the three loci encoding known Fds are subject to distinct regulatory mechanisms and that specific Fds are utilized to shuttle electrons to separate respiratory and energy production complexes during different physiological states. The results obtained argue that unique physiological roles have been established for each Fd and that continued use of T. kodakarensis and related hydrogen-evolving species as bioengineering platforms must account for the distinct Fd partnerships that limit flux to desired electron acceptors. Extrapolating our results more broadly, the retention of multiple Fd isoforms in most species argues that specialized Fd partnerships are likely to influence electron flux throughout biology. High-energy electrons liberated during catabolic processes can be exploited for energy-conserving mechanisms. Maximal energy gains demand these valuable electrons be accurately shuttled from electron donor to appropriate electron acceptor. Proteinaceous electron carriers such as ferredoxins offer opportunities to exploit specific ferredoxin partnerships to ensure that electron flux to critical physiological pathways is aligned with maximal energy gains. Most species encode many ferredoxin isoforms, but very little is known about the role of individual ferredoxins in most systems. Our results detail that ferredoxin isoforms make largely unique and distinct protein interactions in vivo and that flux through one ferredoxin often cannot be recovered by flux through a different ferredoxin isoform. The results obtained more broadly suggest that ferredoxin isoforms throughout biological life have evolved not as generic electron shuttles, but rather serve as selective couriers of valuable low-potential electrons from select electron donors to desirable electron acceptors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

pnnl/ripples

A C++ Library for Influence Maximization Ripples is a software framework to study the Influence Maximization problem. Our goal with Ripples is to provide tools implementing fast and scalable state-of-the-art approximation algorithms to solve the influence maximization problem.

Minutoli, Marco↗
DOE OSTI2023

Data for Controlling Circuitry Underlies the Growth Optimization of Saccharomyces cerevisiae

Microbial growth emerges from coordinated synthesis of various cellular components from limited resources. In Saccharomyces cerevisiae , cyclic AMP (cAMP)-mediated signaling is shown to orchestrate cellular metabolism; however, it remains unclear quantitatively how the controlling circuit drives resource partition and subsequently shapes biomass growth. Here we combined experiment with mathematical modeling to dissect the signaling-mediated growth optimization of S. cerevisiae . We showed that, through cAMP-mediated control, the organism achieves maximal or nearly maximal steady-state growth during the utilization of multiple tested substrates as well as under perturbations impairing glucose uptake. However, the optimal cAMP concentration varies across cases, suggesting that different modes of resource allocation are adopted for varied conditions. Under settings with nutrient alterations, S. cerevisiae tunes its cAMP level to dynamically reprogram itself to realize rapid adaptation. Moreover, to achieve growth maximization, cells employ additional regulatory systems such as the GCN2-mediated amino acid control. This study establishes a systematic understanding of global resource allocation in S. cerevisiae , providing insights into quantitative yeast physiology as well as metabolic strain engineering for biotechnological applications.

Conversion↗
DOE OSTI2021

Attribute-Guided Adversarial Training for Robustness to Natural Perturbations

We report while existing work in robust deep learning has focused on small pixel-level norm-based perturbations, this may not account for perturbations encountered in several real world settings. In many such cases although test data might not be available, broad specifications about the types of perturbations (such as an unknown degree of rotation) may be known. We consider a setup where robustness is expected over an unseen test domain that is not i.i.d. but deviates from the training domain. While this deviation may not be exactly known, its broad characterization is specified a priori, in terms of attributes. We propose an adversarial training approach which learns to generate new samples so as to maximize exposure of the classifier to the attributes-space, without having access to the data from the test domain. Our adversarial training solves a min-max optimization problem, with the inner maximization generating adversarial perturbations, and the outer minimization finding model parameters by optimizing the loss on adversarial perturbations generated from the inner maximization. We demonstrate the applicability of our approach on three types of naturally occurring perturbations --- object-related shifts, geometric transformations, and common image corruptions. Our approach enables deep neural networks to be robust against a wide range of naturally occurring perturbations. We demonstrate the usefulness of the proposed approach by showing the robustness gains of deep neural networks trained using our adversarial training on MNIST, CIFAR-10, and a new variant of the CLEVR dataset.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Study of Integrable and Quasi-Integrable Sextupole Lattice

In order to maximize beam lifetime in circular particle accelerators, the nonlinear beam optics are optimized to maximize the dynamic aperture of the beam. The dynamic aperture (DA), which is a 6-D phase space volume of stable trajectories, depends on the strength of the nonlinearities in the machine, and is calculated via particle tracking. Current DA optimization processes include multi-objective genetic algorithm optimizers, and relies on minimizing the magnitudes of resonance driving terms (RDT), which are calculated from the nonlinear contribution to the one-turn-map. The process of searching through the parameter space for an ideal combination that maximizes DA is computationally strenuous. By setting up the sextupole channel such that it is resembles a symplectic integrator of a smooth Hamiltonian, with only a few sextupoles we are able to closely reproduce phase space trajectories of a smooth Hamiltonian up to the hyperbolic point. No chaos and resonances are observed if phase advance per one sextupole magnet in the channel does not exceed ~0.12x2 pi. Therefore, an important property of the suggested approach is the intrinsic elimination of the resonances, and minimization of corresponding RDTs.

43 PARTICLE ACCELERATORS↗
DOE OSTI2019

Conversion of Coal Wastes and Coal Plus Other Opportunity Fuel Mixtures, Such as Coal Plus Municipal Solids, to Produce Electricity and/or Liquid Fuels

For the foreseeable future, the Nation’s energy demand will continue to come largely from indigenous fossil energy resources and hydrocarbon fuels. Specifically waste coal plus other opportunity fuels need to be utilized as a feedstock to eliminate a waste stream and optimized to maximize energy yield and cleanly minimize pollutant emissions. Modular equipment is needed for installation in coal preparation locations, military installations, and research park facilities. Thermal decomposition of coal, biomass, and mixed solid waste (MSW) have been shown to reduce a waste stream while providing liquid and gaseous fuel products with low pollutant emissions. However, thermal decomposition processes have several challenges associated with preprocessing biomass and MSW, feeding and conveying material into the reactor, and post processing of syngas to remove undesirable products while upgrading to increase yield of high value products. Increasing total energy output from power plants by utilizing biomass and mixed wastes ultimately lowers energy costs, harmful environmental impacts of emissions, and has significant impacts on the energy security and sustainability of the U.S. economy. Entrained flow gasifiers (EFGs) produce very little CH4 and a wide range of H2/CO ratios (0.5–2.0) but are limited in their ability to effectively feed large biomass or MSW particles into the reactor. A solution to the feeding problems is to use pyrolysis torrefaction (PT) for conversion of waste materials to create a feedstock similar to coal and capable of grinding down and mixing with the coal feed. Mainstream experimentally explored reaction pathways for the conversion of coal waste plus municipal solids (CWPMS) and demonstrated a bench-scale reactor used for torrefaction of the municipal solid waste (MSW) to create a coal-like feed for blending with the coal waste. The material was processed in a pilot-scale EFG to determine product yield and emissions with CWPMS fuels, as well as the ash content and slagging properties of these feedstocks. The PT-EFG system was experimentally validated, where emissions and yield data were used to develop a high-fidelity process model and economic analysis. The following was accomplished in the Phase I: Determined optimal torrefaction process conditions for MSW and biomass through TGA; maximized heating value of fuel while maximizing final mass of torrefied product Demonstrated torrefaction of MSW and biomass feedstocks at 334°C, pulverized to uniform 74 µm particle size, and processed into coal-like feedstocks Demonstrated 8 lb/h pilot-scale EFG using MSW and biomass blends with waste coal; demonstrated 100% biomass in EFG Determined major effects of MSW torrefaction and co-gasifying high-ash coal waste-MSW blends have on pilot-scale EFG Demonstrated blending low-ash, low-sulfur torrefied biomass with high-ash waste bituminous and anthracite refuse coals generates a higher quality syngas compared to syngas from high-ash waste coals Demonstrated a high carbon conversion (> 99.5%) and syngas with 29.47% H2 content, and 0% CH4 content; greater water–gas shift occurs in EFG than predicted by equilibrium ASPEN Plus model Blended lower-ash, high-alkali biomass MSW to lower slag viscosities of the high-ash coal refuse sufficiently for better slag flow compared to feeding the high-ash coal Used low-sulfur biomass to greatly reduce the EFG syngas H2S concentrations and produce non-leachable slag and quench water with very little organic and trace metal contamination Developed a process model and TEA showing the modular PT EFG is cost competitive to existing power plants with the advantage of using low- or negative-value feedstocks such as waste coal stockpiles and non-landfilled MSW; providing a large incentive to implement an economical PT-EFG process

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2019

Catalytic Upgrading of Thermochemical Intermediates to Hydrocarbons (Final Report)

A lot of activity in catalytic pyrolysis and hydroprocessing occurred in the past 10-15 years with notable successes and failures; however, very little technical information is available in the open literature from pilot-scale studies such as those performed in this project. Besides, the next step along the technology commercialization pathway is to scale-up the catalytic biomass pyrolysis process, integrate this technology with a hydroprocessing unit, and demonstrate the long-term operation and performance of the integrated process; notably, these were achieved in this project. RTI International has developed a single-step catalytic biomass pyrolysis process to produce a hydrocarbon-rich bio-crude intermediate. This bio-crude is more thermally stable and has lower oxygen content than conventional biomass fast pyrolysis oil, so it can be effectively and efficiently upgraded with traditional hydroprocessing technology to produce gasoline and diesel. Our partner, Haldor Topsøe, has developed a strategy for hydroprocessing bio-crude intermediates based on extensive catalyst and process development in support of converting vegetable oils and waste greases into high-quality diesel fuel. The goal of the originally proposed project was to demonstrate an advanced biofuels technology that integrates a catalytic biomass pyrolysis step and a hydroprocessing step to produce infrastructure-compatible biofuels. The specific technical goals of this project were 1) to optimize the catalytic biomass pyrolysis process to achieve high degree of deoxygenation, while maximizing the bio-crude production, 2) improve bio-crude thermal stability, 3) evaluate the impact of bio-crude quality in the hydroprocessing step, 4) minimize hydrogen demand of the integrated process, and 5) maximize biofuels yields. This project showed that it is technically feasible to use non-zeolitic solid acid catalyst to consistently generate bio-crude with 20% oxygen content and that these liquids can be effectively hydrotreated into low oxygen fuel blendstocks. The reproducibility of the small-scale pyrolysis yields at the 1 tonne/day scale is an achievement worth noting and the effect of pyrolysis temperature on biocrude yields and quality was investigated at the pilot scale. Additionally, advanced analytical techniques were used to analyze bio-crude to investigate the effect of process conditions and feedstock on the concentration and speciation of oxygen-containing compounds. Insights into the impact of oxygen content and oxygen speciation on bio-crdue upgrading were also sought. Clearly, more successful upgrading correlated with bio-crudes with lower oxygen content. This was most evident when partially upgraded bio-crude with 55-90% less oxygen compared to the starting bio-crude was blended with straight run diesel and hydrotreated without any noticeable increase in pressure drop across the reactor or any measurable loss of hydrodenitrification (HDN) activity. Minimizing hydrogen demand while maximizing biofuels yield are the desired outcomes for the integrated process. In summary, several technical challenges remain before catalytic biomass pyrolysis becomes a commercial reality, most notably bio-crude yields and quality still need to be improved. The integrated catalytic biomass pyrolysis hydroprocessing scheme being developed produces intermediates that can be refined for use as drop-in hydrocarbon replacement fuels. From a technology perspective, this advanced biofuel technology produces liquid transportation fuels that can leverage capital expenditures in the existing petroleum refining and distribution infrastructure. From a business perspective, this technology does not face potential market limitations as other nonhydrocarbon biofuels caused by oxygenated blending limitations and fuel certification for light-duty vehicle applications.

09 BIOMASS FUELS↗
DOE OSTI2020

Austin Sustainable and Holistic Integration of Energy Storage and Solar PV [Austin SHINES]. Final Report, Version 2

The Austin SHINES project and solution is a software management platform, for an electric grid with a high penetration of dispersed photovoltaic (PV) solar generation sites, which maintains the traditional power quality and reliability associated with grid service. This project developed and deployed the platform as a Distributed Energy Resource Management System (DERMS), engaging multiple advanced controls, to evaluate operation and optimization of a fleet of diverse DER assets, installed at several locations among Austin Energy’s customers and distribution system. The project also produced a methodology to create a replicable DERMS template, adaptable to other regions and market structures. Last, Austin SHINES aimed to demonstrate the solution’s methodology would enable the DER grid ecosystem to serve load at a technical cost (System Levelized Cost of Electricity, or System LCOE) of less than the U.S. Department of Energy SHINES program metric of $0.14/kWh, in a defined boundary, while enabling a high penetration of distributed PV. Research was categorized in 6 reports (Final Deliverables = FD) listed below, with titles and descriptions indicating which area of understanding was investigated: FD-1: System Levelized Cost of Electricity (System LCOE) Methodology The creation and use of the System LCOE to Serve Load metric that encompasses the holistic, system-level costs and benefits of all resources, and enables them to be evaluated based on their ability to support an efficient and low-cost integrated grid ecosystem. FD-2: Software Platform Product Description The creation of new DER control methodologies deployable within a utility-grade software platform that enable DER's to maximize their benefit within a grid, that is capable of serving load enabling a high penetration of distributed PV generation. FD-3: Optimal Design Methodology Optimal design methodologies for individual DER installations that enable utilities to determine the optimal combinations and sizing for individual DER sites. FD-4: Austin SHINES Ownership and Operation Models for DER System Performance A comparison of multiple DER aggregation and ownership methodologies including direct utility control, third-party aggregator, and autonomous. FD-5: Economic Modeling & Optimization A comparison of multiple DER technology mixes and configurations within the distribution system, providing insight into an optimal blend of technologies that best enable the distribution system to serve load at the lowest cost at high penetrations of solar. FD-6: Fielded Assets Deployed DER assets within the Austin Energy SHINES circuits. Austin SHINES provided an opening for state-of-the-art technology products to be deployed, providing a rich opportunity for improving how each of the products perform as stand-alone products, and in concert with other complementary products. The Austin SHINES project comprised of two key metrics for System LCOE: SystemLCOE_SHINES<$0.14/kWh Modeled ΔSystemLCOE_SHINES/ΔSystemLCOE_Base≥20% at same solar penetration The System LCOE calculation uses the costs of the utility-owned infrastructure as it exists today, the cost of the DERs that exist in the system today, and the cost of the purchase of energy from ERCOT wholesale markets over the course of the calendar year. All costs are on an annualized basis. The capital and operating costs are derived from the rate case, which produces a yearly cost. The net cost of energy and services imported to the system is integrated over the test year, as is the load served and solar penetration. The first metric was easily achieved by every scenario considered. The goal was set when the Department of Energy’s SHINES Funding Opportunity Announcement was written in 2015 and was a more difficult target at the time. Due mostly to rapidly declining costs for DERs and the significant decrease in the Electric Reliability Council of Texas (ERCOT) energy market prices, which results in lower net cost of energy purchases, the System LCOE is well below this target for all scenarios considered. A fleet of DERs can assume different mixtures, each of which serves the load at a different LCOE. The optimal mixture of DERs serves load at the smallest System LCOE. The second metric (hereinafter %delta metric) asks that the holistic DERMS controls reduce the incremental cost above the baseline of going to a high solar penetration future by at least 20% as compared to the case of a DER deployment with no sophisticated controls (autonomous). Many comparison sets were created throughout this project. Physical technology was installed for informing utility engineering and testing several types of operational control schemes, through the DERMS. The types of operational control which were compared for valuation of the System LCOE Metric were: Holistic control = using the full suite of the DERMS platform to decide and optimize how/why the systems operate depending on weather, market, and reliability signal input. Autonomous control = a local mode at the asset site, wherein a schedule operates the asset, with visibility into performance only No control = the baseline for comparing value against the other two types of control The types of ownership control included: Direct Utility control = the utility dispatches a signal to each asset Third-Party Aggregator = a third party aggregates a fleet of assets and the utility dispatches one signal for all Autonomous = a local mode is set for operation at the asset site, wherein a schedule operates the asset, with visibility into performance only The types of control methodologies deployable within a utility-grade software platform included: Utility Peak Load Reduction = Lower transmission cost obligation Day-Ahead Energy Arbitrage = Realize economic value through price differential Real-Time Price Dispatch = Realize economic value from real-time price spikes Voltage support = Reduce losses and increase solar generation Distribution Congestion Management = Increase local grid reliability Demand Charge Reduction = Lower customer bills and realize system benefit The fielded assets deployed for the project were: Utility Scale Kingsbery Energy Storage System: 1.5 MW / 3 MWh Li-Ion battery storage Mueller Energy Storage System: 1.75 MW / 3.2 MWh Li-Ion battery storage, 7 Energy Storage Units (250 kW each) La Loma Community Solar: 2.6 MW Commercial Scale Aggregated storage installations at 3 sites, with existing solar (300+ kW): One 18 kW / 36 kWh Li-Ion battery storage Two 72 kW / 144 kWh Li-Ion battery storage Residential Scale Aggregated storage installations: -Six stationary battery storage systems (10 kWh each) at homes with existing solar -One Electric Vehicle installed as Vehicle-to-Grid (V2G) Utility-Controlled Solar via Smart Inverters at 12 homes Autonomously-Controlled Smart Inverters at 6 homes Over the course of the project, Austin SHINES undertook installing more than 3 MW of distributed battery energy storage, smart PV inverters, a DER control platform, and other enabling technologies utilizing customer and utility locations and aggregation models. All of these resources were to be integrated and optimized at the utility level. DER assets and control methodologies were designed to achieve a credible pathway to a System LCOE for energy delivered to load of $0.14//kWh or less by 2020, while maximizing distributed solar generation and maintaining acceptable standards of power quality. The project also established a template for other regions to follow, to maximize the adoption of distributed solar PV in support of an economic and efficient grid. In total, the Austin SHINES project added value to the DER subject area in each layer of integration. From utility, to commercial to residential scales, the sheer hierarchy of communication and coordination was a significant accomplishment in addition to learnings from what these communications revealed was unique to each. Economically, the most effective method demonstrated was the criticality of planning phases. Contingencies and multiple projection scenarios helped guide the project to deploy optimal design as close as feasible, in real world conditions. The project and reports will serve public benefit by outlining specific areas of DER strategy and installation where many stakeholders and needs can be addressed with improved efficiency. Overall, communities and utilities should use the results to guide the increasing options available for powering the grid with DER, renewables, and carbon considerate energy.

14 SOLAR ENERGY↗
DOE OSTI2023

Demonstration of Scaled-Production of Rare Earth Oxides and Critical Materials from U. S. Coal-Based Sources (Final Report)

The project objective was to demonstrate scaled production of high purity rare earth oxides (REO), nominally exceeding 90% grade, from coal refuse sources using innovative technologies that reduce cost and improve environmental outcomes relative to traditional rare earth processing technologies. The project utilized a critical material pilot plant constructed and tested as part of a previous U.S. Department of Energy project. Target performance criteria was a 50% reduction in production cost based on previous optimum values, 150% increase in recovery and greater than 2% concentrates of rare earth oxides, cobalt and manganese. Concentrate production goals were to produce a rare earth mix oxide product at a rate of 200 grams per day having a minimum purity of 50% as well as products of cobalt and manganese having a minimum purity of 2%. A previous pilot plant investigation identified acid cost as the major contributor to an operating cost that made the recovery of rare earth and other critical metals from bituminous coal sources economically challenging. As such, acid cost reduction was a major target using bio-oxidation reactors to produce sulfuric acid from naturally occurring coal pyrite. Based on laboratory data, a bio-oxidation circuit was designed for the pilot plant to produce 7.5 l/min of acid using two 11-m3 (3000 gallon) reactors equipped with 40 hp aerators for air dispersion. The pilot-scale tests revealed that acid concentration equivalent to as high as 1.0 M sulfuric acid could be continuously produced. However, the bio-acid contained exceptionally high iron concentrations, which complicated downstream processing of the pregnant leach solution (PLS). A TEA of the bio-oxidation circuit showed that production cost was approximately $0.13 per kg acid equivalent if produced using a four-day retention time in the reactors. This value represents a 48% reduction from that of purchased bulk sulfuric acid. Calcination (or roasting) studies were conducted on coarse refuse from West Kentucky No. 13 and Fire Clay coal seam sources. The test results revealed the potential to increase recovery by nearly 100% using temperatures between 500°C to 700°C with light REE recovery value being the most improved. Acid baking of the calcined products using sulfuric acid at 250°C increased heavy rare earth recovery from around 40% to 80% while decreasing the acid requirements by over 50%. The existing pilot plant was upgraded for the pilot scale demonstration of REE and CM recovery. The primary feedstocks were West Kentucky No.13 and heap leach pregnant leach solution (PLS) while a secondary feedstock was a lignite waste material from a construction sand operation. The pilot scale operation started with PLS generation through leaching followed by iron and aluminum removal, nominally at 3.3 and 4.5 pH, respectively. Leaching lixiviants used for the test were industrial grade sulfuric acid or bio-acid generated at the pilot scale facility. For most of the tests, the solid feed rate was 200 lb/hr whereas lixiviant was added at 2 gpm to provide an optimal residence time of 45 minutes. Following the contaminant removal step, several different process schematics were tested with the goal of maximizing REE recovery and purity. In the first test, direct processing of aluminum precipitation raffinate for REE recovery using oxalic acid at pH 1.5 was investigated. Overall REE recovery was approximately 45%. Unfortunately, elevated calcium content in the PLS significantly impacted the RE-Oxide product grade. Similarly, high calcium content decreased both the product purity and grades of CM products. As such, a new flowsheet was tested with the same initial process schematic but different precipitation stages for REEs and CMs at pH 6.0 and 9.0, respectively. It was noted that the overlapping precipitation behavior of Co, Ni and Zn with REEs limited the applicability of this process schematic. While this change increased the RE-Oxide grade from 36% in the first test to 87%, the loss of critical metals to the REE cake and bypass of the REEs to the CM cake significantly impacted the recovery of both REEs and CMs. Therefore, the modified process flowsheet combined oxalic acid precipitation stage raffinate and redissolved CM cake filtrate to maximize both the recovery and purity of the products. Consequently, a RE-Oxide product with 85% purity and CM cakes with over 19% Co, 38% Ni, 14% Zn and 9% Mn content were generated with significantly higher recoveries. While the modified process flowsheet improved recoveries and grades, elemental losses observed in separate precipitation and redissolution losses inspired the adaptation of a single precipitation stage at pH 9.0 for both REEs and CMs. This change was anticipated to maximize the REE recovery while minimizing the costs associated with separated redissolution and processing stages. As expected, REE recovery in this new circuit arrangement was over 56% with a product grade of over 87% RE-Oxide content. Similarly, Co, Ni, Mn, and Zn recoveries of 54%, 40%, 67%, and 66%, respectively, were achieved. Unfortunately, the elevated calcium content present in the solution due to its precipitation at pH 9.0 caused a decrease in the CM cake quality. Therefore, the final process flowsheet involved the addition of calcium oxalate precipitation following the oxalic acid precipitation stage, which effectively eliminated calcium contamination of the CM products. Finally, the pilot scale experiments conducted using bio-acid achieved comparable REE leaching recoveries to the conventional sulfuric acid leaching. Elevated iron concentration in the solution caused the co-precipitation of REEs with the iron and aluminum cake, resulting in the REE losses. Furthermore, elevated iron content bypassing the iron and aluminum precipitation stages contaminated the metal sulfide and manganese cake, respectively. A techno-economic analysis was performed based on a commercial facility capable of treating 500 tph of coal-based material. The production cost for West Kentucky No. 13 coarse refuse material ranged from approximately $500-$700/kg of total rare earth oxide whereas the lignite source had significantly lower production cost of $100-$300/kg. The significant difference in cost was due to the easier leaching characteristics of the lignite material and the higher feed concentrations. All process scenarios resulted in a negative net present value (NPV). For the lignite feedstock, laboratory REE leach recovery values were about 30% higher than the pilot plant data. Using the lab leach results, a positive net present value was achieved and the production cost decreased from $100-$300 $/kg to less than $150/kg of total REO.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Application of Partial Least Squares Approaches to Pyroprocessing ER Data

Multivariate approaches show promise for application to process monitoring for safeguards of pyroprocessing. Past MPACT work explored the application of Principal Component Analysis (PCA) to detect off-normal conditions in pyroprocessing electrorefiner (ER) data from in the Hot Fuel Examination Facility (HFEF) at Idaho National Laboratory (INL) known as the Scalable Pyrochemical Recycling testbed (SPyRe) ER. PCA, however, does not consider the output variables. In FY24, multivariate analysis was extended from PCA to Partial Least Squares (PLS) analysis. PLS maximizes the variance between both the input signals and output variables. In the case of this work, PLS was applied in two different manners: Predictive PLS and Discriminant PLS. Predictive PLS maximizes the covariance between the process variables of the ER and the measured U concentration from in-situ voltammetry. Discriminant PLS maximizes the covariance between the process variables and a set of training process “states” such as known off-normal conditions. By projecting into the latent variable space in PLS, the process variables can be regressed onto the outputs and predictions can be made for new data sets. In this work, by applying predictive PLS, a penalized non-linear PLS approach was able to make predictions of concentration based on test and training data and detect when operations were off-normal. However, the predictive PLS does not classify the signals to which off-normal operations are attributable. Discriminant PLS can be used to classify off-normal operations but is inadequate to properly classify specific off-normal classes like power supply faults when the Discriminant PLS model is only specifically trained to detect that off-normal class. When all faults are trained against the observation data, all three operational classes are accurately classified and distinguished. Thus, future application of latent variable techniques should not select any given method, but should use a mixture of PCA, Predictive PLS, and Discriminant PLS.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1972

Basic Economic Principles

An economic approach to design efficient transportation systems involves maximizing an objective function that reflects both goals and costs. A demand curve can be derived by finding the quantities of a good that solve the maximization problem as one varies the price of that commodity, holding income and the prices of all other goods constant. A supply curve is derived by applying the idea of profit maximization of firms. The production function determines the relationship between input and output.

Tideman, T. N.↗
NASA NTRS1975

A counter example in linear feature selection theory

The linear feature selection problem in multi-class pattern recognition is described as that of linearly transforming statistical information from n-dimensional (real Euclidean) space into k-dimensional space, while requiring that average interclass divergence in the transformed space decrease as little as possible. Divergence is the expected interclass divergence derived from Hajek two-class divergence; it is known that there always exists a k x n matrix B such that the transformation determined by B maximizes the divergence in k-dimensional space. It is known that, if Q is any k x k invertible matrix, and B is as defined above, then QB again maximizes the divergence in k-space. It is shown that the converse of this result is false: two matrices exist, B sub 1 and B sub 2, each of which maximizes transformed divergence, which are not related in the fashion B sub 2 = QB sub 1 for any k x k matrix Q.

Brown, D. R.↗
NASA NTRS1975

Frequency and duration of interval training programs and changes in aerobic power

The present study was designed to ascertain whether a training frequency of 2 days/wk for a 7- and 13-wk interval training program would produce improvement in maximal aerobic power comparable to that obtained from 7- and 13-wk programs of the same intensity consisting of 4 training days/wk. After training, there was a significant increase in maximal aerobic power that was independent of both training frequency and duration. Maximal heart rate was significantly decreased following training. Submaximal aerobic power did not change with training, but submaximal heart rate decreased significantly with greater decreases the more frequent and the longer the training.

Fox, E. L.↗
NASA NTRS1976

On signal design by the R sub 0 criterion for non-white Gaussian noise channels

The use of the R sub 0 criterion for modulation system design is investigated for channels with non-white Gaussian noise. A signal space representation of the waveform channel is developed, and the cut-off rate R sub 0 for vector channels with additive nonwhite Gaussian noise and unquantized demodulation is derived. When the signal unput to the channel is a continuous random vector, maximization of R sub 0 with constrained average signal energy leads to a water-filling interpretation of optimal energy distribution in signal space. The necessary condition for a finite signal set to maximize R sub 0 with constrained energy and an equally likely probability assignment of signal vectors is presented, and an algorithm is outlined for numerically computing the optimum signal set. A necessary condition on a constrained energy, finite signal set is found which maximizes a Taylor series approximation of R sub 0. This signal set is compared with the finite signal set which has the water-filling average energy distribution.

Bordelon, D. L.↗
NASA NTRS1977

Tailcone on orbiter altitude attainable at the maximum ALT interface airspeed

A preflight analysis performed for verification of the ALT mated vehicle incidence angle which maximizes the post separation altitude attainment by the orbiter at the maximum approach and landing test (ALT) interface airspeed (300 KEAS) is discussed. In the analysis, altitude versus airspeed profiles are generated for each of the three incidence angles that include and bound the recommended incidence angle for both the forward and the aft cg tailcone on orbiter configurations. Results show that the recommended incidence angles maximize the orbiter post separation altitude attainable within an acceptable tradeoff between separation clearance capability and orbiter structural constraints. Within constraints, the incidence angle that maximizes the orbiter altitude at the maximum ALT interface airspeed for both the forward and aft cg orbiter tailcone on configurations is 6.0 deg. The requirement for a parametric analysis of orbiter altitude attainable at the maximum ALT interface airspeed is stated along with the specifications, assumptions, and analytical approach used to determine orbiter altitude attainable at the maximum ALT interface airspeed.

Glenn, G. M.↗
NASA NTRS1977

Plasma /Na+/, /Ca++/, and volume shifts and thermoregulation during exercise in man

Graded-exercise experiments are conducted on six trained male runners (19-23 yr) subjected to ergometer exercise in a program consisting of 30-min resting control period, 60 min of rest or exercise at work loads that resulted in a maximal oxygen uptake equivalent to 6% (resting), 23%, 43%, and 62% of maximal oxygen uptake, followed by 30 min of recovery. The parameters measured and discussed are rectal temperature (T-re), skin temperatures at different spots, maximal oxygen uptake, plasma volume (PV), and various plasma electrolyte and protein concentrations. The objectives are to determine whether the increased T-re during progressively greater work loads are related to plasma sodium ion and calcium ion concentrations, as well as to evaluate the influence of PV shifts on the electrolyte and osmotic concentrations. The results suggest that the shift (loss) in PV accounts for the increases in the plasma constituent concentrations that result in significant correlations with T-re.

Greenleaf, J. E.↗
NASA NTRS1982

Induced venous pooling and cardiorespiratory responses to exercise after bed rest

Venous pooling induced by a specially constructed garment is investigated as a possible means for reversing the reduction in maximal oxygen uptake regularly observed following bed rest. Experiments involved a 15-day period of bed rest during which four healthy male subjects, while remaining recumbent in bed, received daily 210-min venous pooling treatments from a reverse gradient garment supplying counterpressure to the torso. Results of exercise testing indicate that while maximal oxygen uptake endurance time and plasma volume were reduced and maximal heart rate increased after bed rest in the control group, those parameters remained essentially unchanged for the group undergoing venous pooling treatment. Results demonstrate the importance of fluid shifts and venous pooling within the cardiovascular system in addition to physical activity to the maintenance of cardiovascular conditioning.

Convertino, V. A.↗