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Si reduction, purification and sheet generation work has been concentrated on gaining information about a reduction process combined with purification (higher purity arc furnace with gas blowing and gradient freezing), transport process with purification and polycrystal sheet growth potential (SiF2), plastic deformation for sheet generation, and float zone sheet recrystallization.
An overview of recent developments in process-control technology which might have applications in future advanced life support systems for long-duration space operations is presented. Consideration is given to design criteria related to control system selection and optimization, and process-control interfacing methodology. Attention is also given to current life support system process control strategies, innovative sensors, instrumentation and control, and innovations in process supervision.
The operations analysis and equipment evaluations pertinent to the design of an automated production facility capable of manufacturing beam-lead CMOS integrated circuits are reported. The overall plan shows approximate cost of major equipment, production rate and performance capability, flexibility, and special maintenance requirements. Direct computer control is compared with supervisory-mode operations. The plan is limited to wafer processing operations from the starting wafer to the finished beam-lead die after separation etching. The work already accomplished in implementing various automation schemes, and the type of equipment which can be found for instant automation are described. The plan is general, so that small shops or large production units can perhaps benefit. Examples of major types of automated processing machines are shown to illustrate the general concepts of automated wafer processing.
The Cryogenic Carbon Capture™ (CCC) process significantly decreases cost and energy demands for CO 2 separation and pressurization to 150 bar compared to alternatives. The process is a post-combustion technology that cools CO 2 -laden flue gas to desublimation temperatures (-100 to -135 °C), separates solid CO 2 —that forms from the flue gas—from the light gases, uses the cold products to cool incoming gases in a recuperative heat exchanger, compresses the solid/liquid CO 2 to final pressures (100–200 bar), and delivers a compressed CO 2 stream separated from an atmospheric pressure light-gas stream. The overall energy and economic costs are about 30-50% lower than most competing processes that involve air separation units (ASUs), solvents, or similar technologies. In addition, the CCC process enjoys several ancillary benefits, including (a) it is a minimally invasive Bolton technology, (b) it provides highly efficient removal of most pollutants (Hg, SOx, NO 2 , HCl, etc.), and (c) possible energy storage capacity. This report outlines the process details and economic and energy comparisons relative to other well-documented alternatives. This paper presents the results of a detailed techno-economic comparison of CCC with amine-based systems. The comparison uses identical financial and economic assumptions similar process assumptions as the detailed analyses published by US DOE in the greenfield analysis. Specifically, the comparison assumes power plants that produce the same net output, one equipped with and a second without carbon capture. Separately, the paper compares similar analyses for retrofitting existing systems using typical plant characteristics in the US (initial capital costs have been paid, high plant utilization), though there are no DOE estimates available for direct comparison. Financial and technical assumptions for all comparisons are maintained as close to the DOE reference studies as possible. The results demonstrate about 30-50% lower costs and energy demands for capture from greenfield coal plants. Natural gas plants produce substantially lower CO 2 concentrations which makes the cost of capturing a ton of CO 2 at the same capture rate as the coal plant higher for all processes while the cost of CO 2 capture per unit of power generation is lower. However, CCC maintains about the same absolute energy and cost advantages for NG as for coal compared to amine systems. Finally, the costs of retrofitting a station are compared to those of building a new station with and without capture. The retrofit costs are comparable to (slightly lower than) new plant costs without capture. In all cases operating and capital cost comparisons show that the CCC process can be retrofitted to a variety of plants to cost effectively reduce CO 2 emissions. Further process integration into the upstream processes and unique process features like water recovery, and integrated energy storage bring the effective cost of carbon capture using the CCC process down further and increase its advantages over alternatives. This technoeconomic analysis shows that the CCC process has the potential to the be lowest cost carbon capture technology under development today.
Industrial Cyber-Physical Systems (ICPS) are an essential backbone of national critical infrastructures. They help monitor and control crucial cyber-enabled services such as energy generation. Commonly ICPS monitors the physical process through Supervisory Control and Data Acquisition (SCADA) systems. The SCADA ecosystem takes critical real-time and future system operational decisions based on the runtime state behavior of field sensors. Traditional SCADA systems use legacy and insecure communication protocols such as the Modbus protocol that lack adequate security mechanisms to provide robust runtime state behavior assurance of constrained field sensors. Therefore, constrained field sensors are commonly vulnerable to standard semantic attacks that gradually change the behavior state of infected devices. This paper discusses process integrity assurance techniques necessary to enhance the security of behavior-based protocols such as the Modbus protocol. The Runtime State Verification (RSV) protocol proposed in this paper aims to address semantic attacks in the SCADA ecosystem by integrating behavior-based Mandatory Results Automata (MRA) and a Hyperledger Fabric (HLF) network. The RSV protocol provides high process integrity assurance through enhanced behavior-based MRA suitable for the constrained field devices. A proof of concept of the RSV protocol has been evaluated in an emulated water-tube boiler. Preliminary evaluations of the RSV protocol aimed to measure the efficiency of the proposed protocol by monitoring an Combustion Efficiency (CE) process necessary to preserve optimal combustion, thus minimizing costs and future maintenance of water-tube boilers. We analyze the overall network overhead and latency of the proposed RSV protocol by evaluating the HLF network performance and comparing the proposed RSV protocol with the state-ofart BloSPAI protocol. Through the preliminary evaluations of the proposed RSV protocol, this paper demonstrates that the proposed RSV protocol overcomes the shortcomings and network overhead of the BloSPAI protocol by integrating behavior-based authentication through novel MRAs and HLF networks.
The widescale consumer adoption of hydrogen fuel cell electric vehicles (HFCEVs) is currently hindered by the high cost of small-scale hydrogen generation and the lack of extensive hydrogen refueling infrastructure. Natural gas-based hydrogen is cheaper when produced in large volumes but is also associated with high CO 2 emissions. To counter these challenges, we propose a hybrid approach where both natural gas and renewables are integrated in a synergistic manner using a dynamic process intensification technology that can be deployed on-site for meeting local demands of refueling stations. The technology is based on sorption enhanced steam methane reforming (SE-SMR) that utilizes a combination of reaction with in-situ CO 2 adsorption for enhancing process modularity, productivity and efficiency thereby outperforming conventional SMR at small scale. We develop a mixed integer linear programming (MILP)-based optimization framework for simultaneous design and scheduling of the SE-SMR process. The simultaneous optimization provides a synergistic combination whereby the renewables allow sustainable hydrogen manufacturing and the dynamic SE-SMR allows optimal use of the intermittency of the renewables. The U.S. nationwide analysis indicates that for futuristic renewable prices and a hydrogen production capacity of 2 ton/day, hydrogen can be produced at 50% less cost compared to the current cost of small-scale hydrogen generation. Finally, the city-wise analysis with varying hydrogen demand shows that even with just 5% HFCEV market penetration level, hydrogen production cost less than $3/kg can be obtained at small scales across the United States with even cheaper hydrogen for large cities.
A totally automated facility for semiconductor oxidation and diffusion was developed using a state-of-the-art diffusion furnace and high temperature grown oxides. Major innovations include: (1) a process controller specifically for semiconductor processing; (2) an automatic loading system to accept wafers from an air track, insert them into a quartz carrier and then place the carrier on a paddle for insertion into the furnace; (3) automatic unloading of the wafers back onto the air track, and (4) boron diffusion using diborane with plus or minus 5 percent uniformity. Processes demonstrated include Wet and dry oxidation for general use and for gate oxide, boron diffusion, phosphorous diffusion, and sintering.
When head motion includes a linear velocity component, eye velocity required to track an earth-fixed target depends upon: a) angular and linear head velocity, b) target distance, and c) direction of gaze relative to the motion trajectory. Recent research indicates that eye movements (LVOR), presumably otolith-mediated, partially compensate for linear velocity in small head excursions on small devices. Canal-mediated eye velocity (AVOR), otolith-mediated eye velocity (LVOR), and Ocular Torsion (OT) can be measured, one by one, on small devices. However, response dynamics that depend upon the ratio of linear to angular velocity in the motion trajectory and on subject orientation relative to the trajectory are present in a centrifuge paradigm. With this paradigm, two 3-min runs yields measures of: LVOR differentially modulated by different subject orientations in the two runs; OT dynamics in four conditions; two directions of "steady-state" OT, and two directions of AVOR. Efficient assessment of the dynamics (and of the underlying central integrative processes) may require a centrifuge radius of 1.0 meters or more. Clinical assessment of the spatial orientation system should include evaluation of central integrative processes that determine the dynamics of these responses.
The UKy-CAER team successfully tested an advanced 0.7 MWe post-combustion CO 2 capture system on a coal-fired power plant using a heat integration process combined with two-stage stripping to enhance the CO 2 absorber performance. One of the unique feature of the UKy-CAER integrated process is a two-stage stripping unit for solvent regeneration. The secondary stripper is empowered by the heat rejection from a conventional steam-heated (primary) stripper. The secondary stripper outlet stream at the commercial scale can be used as boiler secondary combustion air, consequently enriching the flue gas with CO 2 , resulting in less energy penalty required by the CO2 capture system. The primary goal of this study was to form an initial assessment of the impact on the amine solvent from coal combustion flue gas contaminants and the potential higher oxygen content in the solvent due to incorporation of the secondary air stripper into the conventional amine scrubber/stripper system. The overall oxidative degradation was comparable to previous reports with 30 wt% MEA solvent at similar flue gas run hours. This suggests that the addition of the secondary air stripper appears to be negligible with regards to solvent oxidation.
We report the scalable three-dimensional (3-D) integration of functional nanostructures into applicable platforms represents a promising technology to meet the ever-increasing demands of fabricating high performance devices featuring cost-effectiveness, structural sophistication and multi-functional enabling. Such an integration process generally involves a diverse array of nanostructural entities (nano-entities) consisting of dissimilar nanoscale building blocks such as nanoparticles, nanowires, and nanofilms made of metals, ceramics, or polymers. Various synthetic strategies and integration methods have enabled the successful assembly of both structurally and functionally tailored nano-arrays into a unique class of monolithic devices. The performance of nano-array based monolithic devices is dictated by a few important factors such as materials substrate selection, nanostructure composition and nano-architecture geometry. Therefore, the rational material selection and nano-entity manipulation during the nano-array integration process, aiming to exploit the advantageous characteristics of nanostructures and their ensembles, are critical steps towards bridging the design of nanostructure integrated monolithic devices with various practical applications. In this article, we highlight the latest research progress of the two-dimensional (2-D) and 3-D metal and metal oxide based nanostructural integrations into prototype devices applicable with ultrahigh efficiency, good robustness and improved functionality. Lastly, selective examples of nano-array integration, scalable nanomanufacturing and representative monolithic devices such as catalytic converters, sensors and batteries will be utilized as the connecting dots to display a roadmap from hierarchical nanostructural assembly to practical nanotechnology implications ranging from energy, environmental, to chemical and biotechnology areas.
A modular process that can efficiently solve large scale multidisciplinary problems using massively parallel super computers is presented. The process integrates disciplines with diverse physical characteristics by retaining the efficiency of individual disciplines. Computational domain independence of individual disciplines is maintained using a meta programming approach. The process integrates disciplines without affecting the combined performance. Results are demonstrated for large scale aerospace problems on several supercomputers. The super scalability and portability of the approach is demonstrated on several parallel computers.
A modular process that can efficiently solve large scale multidisciplinary problems using massively parallel supercomputers is presented. The process integrates disciplines with diverse physical characteristics by retaining the efficiency of individual disciplines. Computational domain independence of individual disciplines is maintained using a meta programming approach. The process integrates disciplines without affecting the combined performance. Results are demonstrated for large scale aerospace problems on several supercomputers. The super scalability and portability of the approach is demonstrated on several parallel computers.
A set of procedures was developed to enable rapid flight control law deployment and testing on subscale vertical takeoff and landing (VTOL) aircraft. Low-cost, subscale flight vehicles have become well-suited testbeds for rapid flight dynamics and controls research progression; however, integration of custom flight control laws onto flight hardware has historically been an arduous task. The toolchain described in this report leverages Simulink with the UAV Toolbox, a Pixhawk flight computer running PX4 firmware, and QGroundControl to efficiently design and flight test custom control algorithms. A subscale CL-84 VTOL aircraft was used as a testbed in this investigation to exercise the hardware integration process on a physical model. Implementation of custom attitude stabilization control laws and programmed test input excitations for aircraft system identification were demonstrated using the expeditious hardware integration process. The detailed procedures given in this report are expected to be used in future flight test efforts.
Design and operation decisions of manufacturing plants can often be expressed within a hierarchical structure, where optimal decisions at lower operating level provide constraints for the decision raking at a higher decision level. In this work, we are addressing the case of a hierarchical design and scheduling optimization problem. The integration of design and scheduling decisions can play a big role in designing economically profitable plants and improving their operational performance. This problem can be expressed as a bi-level problem, where design related decisions occur at the upper level and operational scheduling decisions at the lower level. Since discrete decisions are involved in both optimization levels, the resulting formulation typically corresponds to bi-level mixed-integer programming problems (B-MIP). The solution of B-MIP problems is very challenging, and typically requires the use of global optimization techniques, with many algorithms not able to guarantee feasibility. To overcome the challenges in solving this class of problems we propose the use of a multi-parametric based algorithm for the solution of bi-level mixed-integer linear and quadratic programming problems, capable of providing the exact and global solution. The main idea of this approach is to treat the lower scheduling problem as a multi-parametric programming problem in which the design decisions are considered as parameters. Here, the resulting parametric solutions can then be substituted into the upper level design problem, which can be solved as a set of single-level deterministic programming problems. Through the developed formulation and algorithm we are able to supply the decision makers with the exact solution of the integrated design and scheduling problem.
Our analyses of sulfate minerals, analog sites, and Martian spectra and spectral images is focused on characterization of the Martian surface and in particular identification of aqueous processes there.
In-Situ Resource Utilization (ISRU) technology is a vital component to NASA’s mission of a sustainable presence on the Moon and Mars. Local resources can be leveraged to reduce resupply frequency and mass. Elements of the Bosch process, combined with the carbothermal reduction process, can produce oxygen on the lunar surface with minimal consumables. The Bosch process can also produce oxygen on the Martian surface by using the CO 2 -rich environment. Between both systems, adsorption pump, solar thermal energy, carbon formation reactor, and water recovery subsystems are modeled and integrated to create a functional model in MATLAB software. The model is used to simulate performance of the system and reduce mass, power, and volume requirements. This integrated system model provides a tool to scale ISRU technologies for oxygen and carbon production. The MATLAB model is created by developing a system of independent subsystem models that are solved for their quasi-steady state values which can be integrated with respect to time to determine the change in current states. A flexible time stepping method is used to ensure a high level of accuracy during periods of rapid change while still making use of a simple explicit integration method. The flexible time step is calculated for each independent subsystem and the minimum value from those is used as the overall time step. A flexible time step is calculated by dividing a resolution value, or the maximum change per time step, by the variables current rate of change. The maximum value from all points in space is used for subsystem models that contain multiple values. The process is done for every variable that is being monitored in each subsystem and the global minimum is used as that iteration’s timestep. Several assumptions used in the MATLAB model for fluid flow dynamics, such as 1-D gas flow through the sorption pump, are supported by modeling in Ansys Fluent software. The Lunar oxygen production system is outlined in Fig. 1. The carbothermal reduction subsystem uses solar energy to heat a mixture of lunar regolith and carbon powder to produce carbon monoxide. To begin, the carbon monoxide feeds to the modified Bosch subsystem along with hydrogen gas. The reactants then enter the carbon formation reactor where water and carbon powder are produced. Solar thermal energy is used to add energy to the reactor, but waste heat from the carbothermal process is another potential heat source. The water is collected and electrolyzed to produce hydrogen which reenters the Bosch subsystem, and the oxygen is stored for downstream use. The carbon powder is collected and feeds back into the carbothermal subsystem. The Martian oxygen production system uses the full Bosch process and is outlined in Fig 2. A CO 2 adsorption pump thermally cycles to scrub and pressurize CO 2 from the environment. Along with an initial supply of hydrogen, the reactants enter the Reverse Water Gas Shift Reactor (RWGSR) which produces carbon monoxide and water. Carbon monoxide and unreacted hydrogen enter the carbon formation reactor to produce water and carbon powder. The water is collected from both reactors and electrolyzed to reintroduce hydrogen and store oxygen for propellant production or life support. Carbon is removed from the carbon formation reactor and stored. The adsorption pump utilizes rapid cycle temperature swings within a stack of zeolite coated surfaces. The subsystem model solves 1-D quasi-steady conservation laws of the quasi-steady form, shown in Eq. 1, for the gas stream and heat exchange liquid to predict performance parameters such as breakthrough capacity and optimum cycle time. The source term S is used to capture interactions between the fluid flows and the sorbent. A quasi-steady-state scheme is used where no time derivatives appear in the governing equations, except for those in the source terms. This results in an autonomous system, where ∂F/∂x = ƒ(F). The fluxes F are provided at the inlet, and an explicit method is used to solve for the spatial distribution of F. The heat and mass flows to the sorbent are then extracted from the source terms. These flows are numerically integrated to produce a 1-D solution for the system’s state as a function of both time and space. The body of the adsorption pump is separated into two semi-independent models: the heat exchanger fluid flow and gas flow through the zeolite coated surfaces. Both models are solved using the above-described method to find a 1-D solution as a function of space and interact only once a timestep is taken. The interaction point is the sorbent through which all heat transfer between the two models must occur. Sorbent mass adsorption is calculated using the Lagergren model, shown in Eq. 2, where the transfer coefficient, λ D , is found by solving a system of nondimensionalized equations derived by using the heat and mass transfer analogy for transport phenomena. Using Grade 544 Type 13X zeolite as the sorbent material, the equilibrium concentration, θ eq , is calculated using the k-site Langmuir isotherm and fit parameters. Additionally, the enthalpy of adsorption used in the model is computed by interpolation of available data [1]. The subsystem model was validated using the Rapid Cycle Temperature Swing Adsorption (RC-TSA) pump. The solar thermal energy subsystem focuses on a solar concentrator concept with a heat exchanger to heat the reactants before entering the carbon formation reactor. The subsystem model assumes a fixed solar flux and reflector efficiency to calculate the reactant temperature given the incoming temperature, pressure, and exchanger geometry. The receiver is a custom manufactured series of copper blocks with serpentine channels to increase its surface area and the residence time of the reactants to heat up to 550 °C. The subsystem model was validated using a heat exchanger developed at NASA Glenn Research Center (GRC). The solar thermal energy subsystem focuses on a solar concentrator concept with a heat exchanger to heat the reactants before entering the carbon formation reactor. The subsystem model assumes a fixed solar flux and reflector efficiency to calculate the reactant temperature given the incoming temperature, pressure, and exchanger geometry. The receiver is a custom manufactured series of copper blocks with serpentine channels to increase its surface area and the residence time of the reactants to heat up to 550 °C. The subsystem model was validated using a heat exchanger developed at NASA Glenn Research Center (GRC).
Understanding of intracellular polymerization of sickle hemoglobin (HbS) and subsequent interaction with the membrane of a red blood cell (RBC) is important to predict the altered morphologies and mechanical properties of sickle RBCs in sickle cell anemia. However, modeling the integrated processes of HbS nucleation, polymerization, HbS fiber interaction, and subsequent distortion of RBCs is challenging as they occur at multispatial scales, ranging from nanometers to micrometers. To make progress toward simulating the integrated processes, we propose a hybrid HbS fiber model, which couples fine-grained and coarse-grained HbS fiber models through a mesoscopic adaptive resolution scheme (MARS). To this end, we apply a microscopic model to capture the dynamic process of polymerization of HbS fibers, while maintaining the mechanical properties of polymerized HbS fibers by the mesoscopic model, thus providing a means of bridging the subcellular and cellular phenomena in sickle cell disease. At the subcellular level, this model can simulate HbS polymerization with preexisting HbS nuclei. At the cellular level, if combined with RBC models, the generated HbS fibers could be applied to study the morphologies and membrane stiffening of sickle RBCs. One important feature of the MARS is that it can be easily employed in other particle-based multiscale simulations where a dynamic coarse-graining and force-blending method is required. As demonstrations, we first apply the hybrid HbS fiber model to simulate the interactions of two growing fibers and find that their final configurations depend on the orientation and interaction distance between two fibers, in good agreement with experimental observations. We also model the formation of fiber bundles and domains so that we explore the mechanism that causes fiber branching.
Not provided.