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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 OSTI2022

Practical Pathways: Assessing Potential Formats for Arms Control with Russia and China

Building off foundational analyses done previously at the Center for Global Security Research at Lawrence Livermore National Laboratory, this paper takes on two daunting tasks - to outline the security policy objectives for future strategic arms control agreements and to provide recommendations on the potential form of such an agreement. This is the proper moment for such an undertaking. Arms control faces a doubtful future as a viable national security tool. Many proposals – either gradual modifications of existing regimes or revolutionary departures into new domains – made over the past decade no longer fit today’s security environment, one shaped by China’s massive force expansion and Russia’s war in Ukraine. With the new complexities of the two-peer environment and the complete rupture in U.S.-Russian relations, people have valid questions about arms control’s forms and functions. New thinking is needed, shaped by guidance from the past, an analysis of the impasse, a spectrum of the possible, and a realistic assessment of the feasible. If progress is to be made, either before the expiration of the New START Treaty in 2026 or during the subsequent interregnum, a concrete proposal must be agreed within the U.S. interagency and put in front of allies and negotiating partners to serve as the basis for future work.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
NASA NTRS1980

Electronic and software subsystems for an autonomous roving vehicle

The complete electronics packaging which controls the Mars roving vehicle is described in order to provide a broad overview of the systems that are part of that package. Some software debugging tools are also discussed. Particular emphasis is given to those systems that are controlled by the microprocessor. These include the laser mast, the telemetry system, the command link prime interface board, and the prime software.

Doig, G. A.↗
NASA NTRS2012

Global Precipitation Measurement (GPM) Safety Inhibit Timeline Tool

The Global Precipitation Measurement (GPM) Observatory is a joint mission under the partnership by National Aeronautics and Space Administration (NASA) and the Japan Aerospace Exploration Agency (JAXA), Japan. The NASA Goddard Space Flight Center (GSFC) has the lead management responsibility for NASA on GPM. The GPM program will measure precipitation on a global basis with sufficient quality, Earth coverage, and sampling to improve prediction of the Earth's climate, weather, and specific components of the global water cycle. As part of the development process, NASA built the spacecraft (built in-house at GSFC) and provided one instrument (GPM Microwave Imager (GMI) developed by Ball Aerospace) JAXA provided the launch vehicle (H2-A by MHI) and provided one instrument (Dual-Frequency Precipitation Radar (DPR) developed by NTSpace). Each instrument developer provided a safety assessment which was incorporated into the NASA GPM Safety Hazard Assessment. Inhibit design was reviewed for hazardous subsystems which included the High Gain Antenna System (HGAS) deployment, solar array deployment, transmitter turn on, propulsion system release, GMI deployment, and DPR radar turn on. The safety inhibits for these listed hazards are controlled by software. GPM developed a "pathfinder" approach for reviewing software that controls the electrical inhibits. This is one of the first GSFC in-house programs that extensively used software controls. The GPM safety team developed a methodology to document software safety as part of the standard hazard report. As part of this process a new tool "safety inhibit time line" was created for management of inhibits and their controls during spacecraft buildup and testing during 1& Tat GSFC and at the Range in Japan. In addition to understanding inhibits and controls during 1& T the tool allows the safety analyst to better communicate with others the changes in inhibit states with each phase of hardware and software testing. The tool was very useful for communicating compliance with safety requirements especially when working with a foreign partner.

Dion, Shirley↗
NASA NTRS2006

Towards a Theory of Sampled-Data Piecewise-Deterministic Markov Processes

The analysis and design of practical control systems requires that stochastic models be employed. Analysis and design tools have been developed, for example, for Markovian jump linear continuous and discrete-time systems, piecewise-deterministic processes (PDP's), and general stochastic hybrid systems (GSHS's). These model classes have been used in many applications, including fault tolerant control and networked control systems. This paper presents initial results on the analysis of a sampled-data PDP representation of a nonlinear sampled-data system with a jump linear controller. In particular, it is shown that the state of the sampled-data PDP satisfies the strong Markov property. In addition, a relation between the invariant measures of a sampled-data system driven by a stochastic process and its associated discrete-time representation are presented. As an application, when the plant is linear with no external input, a sufficient testable condition for the convergence in distribution to the invariant delta Dirac measure is given.

Herencia-Zapana, Heber↗
DOE OSTI2021

BETO 2021 Peer Review - Process Monitoring and Predictions of Biorefinery Performance

Online process monitoring coupled with rapid predictive tools will be essential to refineries of the future to provide real-time feedback and process control on new, renewable feeds and their accompanying processes and products. This project will provide refinery operators with tools to predict product component concentrations in minutes from online, slip stream mass spectra, allowing for rapid detection of off-specification product. We will arrive at a template for predictive tool generation through the development of a specific tool as a starting point -- co-processing of pyrolysis oils and vacuum gas oil over fluid catalytic cracking (FCC) catalysts.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Alfalfa Virtual Building Service: Software Engineering Best Practices Applied to Runtime Interaction with Building Energy Models

Buildings are active participants in increasingly complex energy systems. Building Energy Modeling (BEM) has a key role to play in planning and de-risking an equitable energy transition, with BEM-backed "virtual buildings" critical path for diverse applications that include workforce training tools, Hardware-in-the-Loop (HIL) experimentation to study equipment performance under a range of conditions, Control-Hardware-in-the-Loop (CHIL) experimentation to de-risk commercial control implementations at equipment through grid orchestration levels, and integration of dynamic load profiles into grid modeling tools for energy system experimentation at the urban scale. Modeling requirements vary across these applications, but many software engineering tasks do not. The Alfalfa Virtual Building Service (AVBS, see https://github.com/NREL/alfalfa/wiki) is an open-source web service that solves these common tasks robustly in one place, providing a foundational platform for power users to bootstrap their own applications. AVBS abstracts the specifics of runtime interaction with OpenStudio, Modelica, and Spawn of EnergyPlus models behind a unified REST API. Additionally, AVBS provides resources for cloud deployment and scaling to 100s of parallel simulations, a growing library of modular Operational Technology (OT) integrations for emulation of real-world interfaces, and scripts to automate the population of communities of virtual buildings from URBANopt, ResStock and ComStock.

building automation↗
NASA NTRS2012

Interval Management with Spacing to Parallel Dependent Runways (IMSPIDR) Experiment and Results

An area in aviation operations that may offer an increase in efficiency is the use of continuous descent arrivals (CDA), especially during dependent parallel runway operations. However, variations in aircraft descent angle and speed can cause inaccuracies in estimated time of arrival calculations, requiring an increase in the size of the buffer between aircraft. This in turn reduces airport throughput and limits the use of CDAs during high-density operations, particularly to dependent parallel runways. The Interval Management with Spacing to Parallel Dependent Runways (IMSPiDR) concept uses a trajectory-based spacing tool onboard the aircraft to achieve by the runway an air traffic control assigned spacing interval behind the previous aircraft. This paper describes the first ever experiment and results of this concept at NASA Langley. Pilots flew CDAs to the Dallas Fort-Worth airport using airspeed calculations from the spacing tool to achieve either a Required Time of Arrival (RTA) or Interval Management (IM) spacing interval at the runway threshold. Results indicate flight crews were able to land aircraft on the runway with a mean of 2 seconds and less than 4 seconds standard deviation of the air traffic control assigned time, even in the presence of forecast wind error and large time delay. Statistically significant differences in delivery precision and number of speed changes as a function of stream position were observed, however, there was no trend to the difference and the error did not increase during the operation. Two areas the flight crew indicated as not acceptable included the additional number of speed changes required during the wind shear event, and issuing an IM clearance via data link while at low altitude. A number of refinements and future spacing algorithm capabilities were also identified.

Baxley, Brian T.↗
NASA NTRS2001

Streptococcus pneumoniae PstS production is phosphate responsive and enhanced during growth in the murine peritoneal cavity

Differential display-PCR (DDPCR) was used to identify a Streptococcus pneumoniae gene with enhanced transcription during growth in the murine peritoneal cavity. Northern dot blot analysis and comparative densitometry confirmed a 1.8-fold increase in expression of the encoded sequence following murine peritoneal culture (MPC) versus laboratory culture or control culture (CC). Sequencing and basic local alignment search tool analysis identified the DDPCR fragment as pstS, the phosphate-binding protein of a high-affinity phosphate uptake system. PCR amplification of the complete pstS gene followed by restriction analysis and sequencing suggests a high level of conservation between strains and serotypes. Quantitative immunodot blotting using antiserum to recombinant PstS (rPstS) demonstrated an approximately twofold increase in PstS production during MPC from that during CCs, a finding consistent with the low levels of phosphate observed in the peritoneum. Moreover, immunodot blot and Northern analysis demonstrated phosphate-dependent production of PstS in six of seven strains examined. These results identify pstS expression as responsive to the MPC environment and extracellular phosphate concentrations. Presently, it remains unclear if phosphate concentrations in vivo contribute to the regulation of pstS. Finally, polyclonal antiserum to rPstS did not inhibit growth of the pneumococcus in vitro, suggesting that antibodies do not block phosphate uptake; moreover, vaccination of mice with rPstS did not protect against intraperitoneal challenge as assessed by the 50% lethal dose.

Non-NASA Center↗
DOE OSTI2021

A Cyber-Physical System for Freeway Ramp Meter Signal Control Using Deep Reinforcement Learning in a Connected Environment

Freeway bottlenecks such as on-ramp merging areas account for about 40% of recurring freeway congestion. It is generally agreed that building more roads and adding more lanes to existing infrastructure does not solve the congestion problem, and so dynamic traffic control measures offer a more cost-effective alternative. Ramp meters, traffic signal devices that regulate traffic flow entering freeways, are among the most effective measures to mitigate congestion at on-ramp merging areas on freeways. The confluence of deep reinforcement learning (RL) and connectivity provides a possible solution to advance ramp meter signal control. Deep RL is a group of machine-learning methods that enables an agent learning from the environment to improve its performance. In this study, three deep RL methods-proximal policy optimization (PPO), Ape-X deep Q-network (DQN), and asynchronous advantage actor-critic agents (A3C)-are explored for ramp meter signal control to maximize vehicle speed and traffic throughput, as well as to minimize energy consumption and emissions at freeway on-ramp merging areas in a connected environment. The low computational requirement and scalability of deep RL for deployment make it a powerful optimization tool for time-sensitive applications such as ramp meter signal control. The results of this study show that deep RL methods yield superior performance to both a fixed-time controller and ALINE A, a state-of-the-art feedback controller.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗
DOE OSTI2020

Energy Consumption and Cost Reduction of Future Light-Duty Vehicles through Advanced Vehicle Technologies: A Modeling Simulation Study Through 2050

The U.S. Department of Energy’s (DOE’s) Vehicle Technologies Office (VTO) and Hydrogen and Fuel Cell Technologies Office (HFTO) aim to develop sustainable, affordable and efficient technologies for transportation of goods and people. Translating investments in advanced transportation component technologies and powertrains to estimate vehicle-level fuel savings potential is critical for understanding DOE’s impact. In this work, we simulated technologies funded by VTO and HFTO for light duty vehicles. The simulations were performed across: Multiple powertrain configurations (i.e., conventional, power-split, extended-range electric vehicle, battery electric drive, and fuel-cell vehicles), Vehicle classes (i.e., compact car, midsize car, small sport utility vehicle [SUV], midsize SUV, and pickup trucks); and Fuels (i.e., gasoline, diesel, hydrogen, and battery electricity). These various technologies are assessed for six different timeframes: laboratory years 2015, 2020, 2025, 2030, and 2045. A delay of 5 years is assumed between laboratory year and model year (year technology is introduced into production). Finally, uncertainties are included for both technology performance and cost aspects by considering two cases: Low case, aligned with DOE technology manager estimates of expected original equipment manufacturer (OEM) improvements based on regulations, business as usual; and High case, aligned with aggressive technology advancements based on R&D targets developed through support by VTO & HFTO. These scenarios are not intended as predictions of future performances. The energy and cost impact of different technologies were estimated using Autonomie (www.autonomie.net), Argonne vehicle system simulation tool. Autonomie is a state-of-the-art vehicle system simulation tool used to assess the energy consumption, performance and cost of multiple advanced vehicle technologies across classes (from light to heavy duty), powertrains (from conventional to HEVs, FCEVs, PHEVs and BEVs), components and control strategies. Autonomie is packaged with a complete set of vehicle models for a wide range of vehicle classes, powertrain configurations and component technologies, including vehicle level and component level controls. These controls were developed and calibrated using dynamometer test data. Autonomie has been used to support a wide range of studies including analyzing various component technologies, sizing powertrains components for different vehicle requirements, comparing the benefits of powertrain configurations, optimizing both heuristic and route based vehicle energy control and predicting transportation energy use when paired with a traffic modeling tool such as POLARIS. This report documents the assumptions and estimates the vehicle-level energy consumption benefits and associated technology costs for the various types of light duty vehicles. All details of vehicle assumptions and simulation results are available in the spreadsheets accompanying this report.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRSDate not supplied

What is the Role of Usability and Trust in Autonomy?

Usability encompasses learnability, efficiency, memorability, effectiveness, and satisfaction. NASA’s standards for usability acceptance criteria focus on interfaces that help operators achieve their tasks efficiently, effectively, and with satisfaction. However, discussions on usability, especially regarding future highly automated and autonomous systems, rarely include trust. As NASA plans for long-duration exploration missions, it envisions astronauts operating more independently from Mission Control on Earth. This independence will drive the development of these highly automated and autonomous systems that astronauts will use daily. To prepare for this future, our team has developed a scheduling and execution software tool that facilitates self-scheduling, allowing astronauts to independently manage their own schedule without Mission Control’s involvement. Over many years, we have developed, matured, and evaluated our software tool in extreme environments, prioritizing user-centered design and high usability. These evaluations have included multiple campaigns in NASA analogs, including NEEMO, BASALT, and HERA, as well as technology demonstrations onboard the International Space Station. Our recent research on software interfaces for future astronaut autonomy revealed a strong correlation between usability and trust measures. In a controlled lab experiment, we asked novice users to perform a complex scheduling task, during which the software immediately validated the schedule’s constraints and checked for violations. We collected usability (User Experience Questionnaire, UEQ) and trust (Trust in Automated Systems scale, TAS) measures; significant, strong, and moderate correlations emerged between several of the UEQ metrics and TAS. These results support the argument for investing in usability early to enable and sustain trust in highly automated and autonomous systems.

usability↗
NASA NTRSDate not supplied

Flying Qualities Analysis and Piloted Simulation Testing of a Lift+Cruise Vehicle with Propulsion Failures in Hover and Low-Speed Conditions

The recent emergence of electric-Vertical Take-Off and Landing (eVTOL) vehicles for Urban Air Mobility (UAM) applications has resulted in a wide variety of configurations with unique stability and control characteristics. NASA is currently conducting research to develop conceptual design tools to accelerate public acceptance of these vehicles which includes requirements for safety during failure scenarios. This paper summarizes progress toward a toolbox for predicting flying qualities of eVTOL vehicles during critical propulsion failures that could impact the allowable design of the vehicle geometry or control system. Key topics include unique vulnerabilities of eVTOL/multirotor vehicles to propulsion failures, relevant flying qualities design metrics, and simulation modeling requirements for assessing flying qualities degradation due to failures. Results of a piloted simulation study conducted in the NASA Ames Vertical Motion Simulator (VMS) are presented. The VMS experiment was designed to assess and validate key handling qualities and safety design metrics for propulsion failures. These results show the correlation between control system design requirements and the degradation in handling qualities for various propulsion failures.

George Altamirano↗
DOE OSTI2022

Leveraging Multiple Raman Excitation Wavelength Systems for Process Monitoring of Nuclear Waste Streams

Processing nuclear waste from sites such as Hanford is a significant environmental cleanup need while being a significant logistical challenge. Integration of process monitoring tools, that can provide in situ and real-time feedback about the process, can significantly alleviate needs to collect grab samples for process control and product characterization. Raman spectroscopy paired with chemometric analysis is one process monitoring tool that can provide chemical composition information on a large number of chemical targets in nuclear waste streams. However, methods to improve limits of detection as well as drop uncertainty in quantification are needed. Optimizing instrument specifications can achieve this, here this is demonstrated by comparing limits of detection for key analytes when using Raman systems with 671 nm, 532 nm, and 405 nm excitation wavelengths. Generally, limits of detection decease (allowing the measurement of lower salt concentrations) with decreasing wavelength. Similarly, data collection times and averaging were optimized. Finally, multiple chemometric modeling approaches were leveraged, including multiblock methods that combined data from all three Raman systems to simultaneously quantify targets with improved sensitivity.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2016

Taxi Time Prediction at Charlotte Airport Using Fast-Time Simulation and Machine Learning Techniques

Accurate taxi time prediction is required for enabling efficient runway scheduling that can increase runway throughput and reduce taxi times and fuel consumptions on the airport surface. Currently NASA and American Airlines are jointly developing a decision-support tool called Spot and Runway Departure Advisor (SARDA) that assists airport ramp controllers to make gate pushback decisions and improve the overall efficiency of airport surface traffic. In this presentation, we propose to use Linear Optimized Sequencing (LINOS), a discrete-event fast-time simulation tool, to predict taxi times and provide the estimates to the runway scheduler in real-time airport operations. To assess its prediction accuracy, we also introduce a data-driven analytical method using machine learning techniques. These two taxi time prediction methods are evaluated with actual taxi time data obtained from the SARDA human-in-the-loop (HITL) simulation for Charlotte Douglas International Airport (CLT) using various performance measurement metrics. Based on the taxi time prediction results, we also discuss how the prediction accuracy can be affected by the operational complexity at this airport and how we can improve the fast time simulation model before implementing it with an airport scheduling algorithm in a real-time environment.

airport surface traffic↗
NASA NTRS2013

Surface Inspection Tool for Optical Detection of Surface Defects

The Space Shuttle Orbiter windows were damaged both by micrometeor impacts and by handling, and required careful inspection before they could be reused. The launch commit criteria required that no defect be deeper than a critical depth. The shuttle program used a refocus microscope to perform a quick pass/fail determination, and then followed up with mold impressions to better quantify any defect. However, the refocus microscope is slow and tedious to use due to its limited field of view, only focusing on one small area of glass at a time. Additionally, the unit is bulky and unable to be used in areas with tight access, such as defects near the window frame or on the glass inside the Orbiter due to interference with the dashboard. The surface inspection tool is a low-profile handheld instrument that provides two digital video images on a computer for monitoring surface defects. The first image is a wide-angle view to assist the user in locating defects. The second provides an enlarged view of a defect centered in the window of the first image. The focus is adjustable for each of the images. However, the enlarged view was designed to have a focal plane with a short depth. This allows the user to get a feel for the depth of different parts of the defect under inspection as the focus control is varied. A light source is also provided to illuminate the defect, precluding the need for separate lighting tools. The software provides many controls to adjust image quality, along with the ability to zoom digitally the images and to capture and store them for later processing.

Nurge, Mark↗
NASA NTRS2003

Friction Stir Welding of Tapered Thickness Welds Using an Adjustable Pin Tool

Friction stir welding (FSW) can be used for joining weld lands that vary in thickness along the length of the weld. An adjustable pin tool mechanism can be used to accomplish this in a single-pass, full-penetration weld by providing for precise changes in the pin length relative to the shoulder face during the weld process. The difficulty with this approach is in accurately adjusting the pin length to provide a consistent penetration ligament throughout the weld. The weld technique, control system, and instrumentation must account for mechanical and thermal compliances of the tooling system to conduct tapered welds successfully. In this study, a combination of static and in-situ measurements, as well as active control, is used to locate the pin accurately and maintain the desired penetration ligament. Frictional forces at the pin/shoulder interface were a source of error that affected accurate pin position. A traditional FSW pin tool design that requires a lead angle was used to join butt weld configurations that included both constant thickness and tapered sections. The pitch axis of the tooling was fixed throughout the weld; therefore, the effective lead angle in the tapered sections was restricted to within the tolerances allowed by the pin tool design. The sensitivity of the FSW process to factors such as thickness offset, joint gap, centerline offset, and taper transition offset were also studied. The joint gap and the thickness offset demonstrated the most adverse affects on the weld quality. Two separate tooling configurations were used to conduct tapered thickness welds successfully. The weld configurations included sections in which the thickness decreased along the weld, as well as sections in which the thickness increased along the weld. The data presented here include weld metallography, strength data, and process load data.

Adams, Glynn↗
NASA NTRS1981

A data collection scheme for identification of parameters in a driver model

A high gain steering controller to compensate for limitations in a handicapped driver's range of motion is employed when adapting vehicle to his use. A driver/vehicle system can become unstable as vehicle speed is increased, therefore it is desirable to use a computer simulation of the driver/vehicle combination as a design tool to investigate the system response prior to construction of a controller and road testing. Unknown driver parameters must be identified prior to use of the model for system analysis. A means to collect the data necessary for identification of these driver model parameters without extensive instrumentation of a vehicle to measure and record vehicle states is addressed. Initial tests of the procedure identified all of the driver parameters with errors of 6% or less.

Mooring, B. W.↗
DOE OSTI2019

Improving Energy Efficiency of Air Separation via Hollow Fiber Sorbents

This report summarizes the work performed under the Department of Energy’s National Energy Technology Laboratory (DOE-NETL) Advanced Energy Systems Program award number DE-FE0026163 Improving Energy Efficiency of Air Separation via Hollow Fiber Sorbents. The overall objective of the project was to develop technology to produce oxygen for use in coal gasification processes at a significantly lower cost than that of the commercial state-of-the-art technology. The focus of the project was development and optimization of hollow fiber sorbents for use in a pressure swing adsorption (PSA) process for producing oxygen from air. The key technical advancement under this program was the development of a hollow fiber sorbent capable of producing oxygen in a PSA process. PSAs produce oxygen by using a beaded zeolite material (typically lithium exchanged zeolites or LiX) that selectively adsorb nitrogen over oxygen. For a fiber to adsorb nitrogen, LiX needed to be integrated into a polymer fiber and then activated at over 350C to remove residual moisture. After screening multiple materials and process techniques, Matrimid/LiX hollow fibers were produced that were able to withstand the activation and had crystalline nitrogen capacity close to pure LiX crystals. The fibers were dual layer fibers with a barrier layer isolating the hollow bore from the LiX embedded layer. The barrier layer was formed from an Ultem® based solution. The hollow bore was intended for encapsulating phase change materials to ensure isothermal PSA operation. Modeling work from the project suggested that the benefits of this additional complexity were marginal, thus the team fabricated non-hollow fibers comprised of Matrimid and LiX. The Matrimid/LiX fibers were loaded into a module and tested on a bench scale PSA unit. The fibers were able to separate oxygen from air, but the purity and recovery were lower than expected and lower than traditional beaded LiX zeolites, although modeling results suggested that the bed sizes for fiber sorbents could be half the size of a beaded LiX bed. Additional work will be needed to understand the shortfall and to produce fiber sorbent modules with performance equal to the targets set for this program. In addition to producing fibers, modeling work was carried out at both the fiber level and process level to guide both fiber sorbent development and to determine the optimal process conditions for a PSA using fiber sorbents. A 2D hollow fiber model was developed in gPROMS Model Builder. This model was based on literature data for mass transfer and other parameters. This model used a basic single bed PSA process to determine important fiber properties and process conditions for achieving high oxygen recovery. The preliminary 2D fiber model was a valuable tool, however, for step-out technologies, such as a PSA process with fiber sorbents, intelligent optimization and plant control was needed to effectively determine minimum power designs. Therefore, a gPROMS Process Builder-based optimization tool was developed with an “Automated Cycle Optimizer” model that was able to determine optimal cycle conditions for a fiber sorbent PSA. The results from the optimizer were used in the final power analysis. Flow sheet analysis and techno-economic analysis (TEA) was carried out to determine a lower power solution versus the baseline case. The original project scope suggested that the fiber sorbent PSA could be used to debottleneck a cryogenic air separation plant (cryo-ASU) with the combined plant having lower power than a standalone cryo-ASU. However, early flowsheet analysis showed that the PSA/cryo-ASU concept would not lead to a lower power solution. However, further flowsheet analysis suggested that an oxygen PSA combined with a nitrogen PSA could have lower power versus state-of-the-art air separation technology. Work concluded with the TEA showing a fiber sorbent oxygen PSA combined with an advanced nitrogen PSA could be up to 8% lower power versus the base case cryo-ASU. Overall, there is significant potential remaining for the zeolite hollow fiber sorbent concept, and this project successfully identified -- and ultimately remedied -- many technical challenges associated with scale-up.

01 COAL, LIGNITE, AND PEAT↗