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An instrumentation system exploits laser-induced incandescence (LII) to measure the concentration of soot particles in an exhaust stream from an engine, furnace, or industrial process that burns hydrocarbon fuel. In comparison with LII soot-concentration-measuring systems, this system is more complex and more capable.
One of the most abundant resources available on Mars is the atmosphere. The primary constituent, carbon dioxide, can be used to produce a wide variety of consumables including propellants and breathing air. The residual gases can be used for additional pressurization tasks including supplementing the oxygen partial pressure in human habitats. A system is presented that supplies pure, high-pressure carbon dioxide and a separate stream of residual gases ready for further processing. This power-efficient method freezes the carbon dioxide directly from the atmosphere using a pulse-tube cryocooler. The resulting CO2 mass is later thawed in a closed pressure vessel, resulting in a compact source of liquefied gas at the vapor pressure of the bulk fluid. Results from a demonstration system are presented along with analysis and system scaling factors for implementation at larger scales. Trace gases in the Martian atmosphere challenge the system designer for all carbon dioxide acquisitions concepts. The approximately five percent of other gases build up as local concentrations of CO2 are removed, resulting in diminished performance of the collection process. The presented system takes advantage of this fact and draws the concentrated residual gases away as a useful byproduct. The presented system represents an excelient volume and mass solution for collecting and compressing this valuable Martian resource. Recent advances in pulse-tube cryocooler technology have enabled this concept to be realized in a reliable, low power implementation.
With the explosion of the CubeSat, small sat, and nanosat markets, the need for a robust, highly capable, yet affordable satellite base station, capable of telemetry capture and relay, is significant. The Programmable Ultra-Lightweight System Adaptable Radio (PULSAR) is NASA Marshall Space Flight Center's (MSFC's) software-defined digital radio, developed with previous Technology Investment Programs and Technology Transfer Office resources. The current PULSAR will have achieved a Technology Readiness Level-6 by the end of FY 2014. The extensibility of the PULSAR will allow it to be adapted to perform the tasks of a mobile base station capable of commanding, receiving, and processing satellite, rover, or planetary probe data streams with an appropriate antenna.
Geomorphological and mineralogical data from early Martian surfaces indicate liquid water was present on ancient Mars. The relative surface temperatures, however, remain a subject of debate. Was early Mars warm and wet or cold and icy with punctuated periods of warmth and ice melt? By characterizing the mineralogy and geochemistry of modern icy mafic terrains on Earth, we can search for these characteristics in early Martian terrains to better constrain the early Martian climate. Here, we describe the mineralogy of glacial flour in a modern glaciated volcanic terrain in Oregon, USA. We are particularly interested in secondary phases that form in these environments, and we hypothesize that poorly crystalline phases may preferentially form in these terrains because of the low temperatures and the seasonality of melt water production. A description of the mineralogy of the moraines, the composition of the amorphous materials, and the geochemistry of the glacial melt waters are presented elsewhere. Glacial flour is made up of silt- and clay-sized particles that form from the physical weathering of rock underlying a wet-based glacier as the glacier slides over it. Flour is usually transported from underneath a glacier by melt water streams. The geochemistry of glacial melt water streams has been studied extensively and has been used to infer weathering reactions within glacial systems. However, the mineralogy of these environments, especially on mafic volcanic terrains, is not well studied. Rock flour is a ubiquitous physical weathering product in glaciated terrains and, therefore, affects microbial habitats, stream and lake chemistry, and chemical weathering processes. and by studying the mineralogy of glacial flour, we can better understand geochemical and microbiological processes in subglacial and proglacial terrains.
Free-space laser communications experiments were conducted between the laser communication equipment (LCE) on board the Japanese Engineering Test Satellite VI (ETS-VI) and the ground station located at the Table Mountain Facility (TMF) during late 1995 and early 1996. This article describes the on-line data reduction process used to decode LCE telemetry (called E2) downlinked on the optical carrier during the Ground/Orbiter Lasercomm Demonstration (GOLD) experiments. The LCE has the capability of transmitting real-time sensor and status information at 128 kbps by modulating the onboard diode laser. The optical downlink was detected on the ground, bit synchronized, and the resulting data stream stored on a data recorder. The recorded data were subsequently decoded by on-line data processing that included cross-correlation of the known telemetry data format and the downlink data stream. Signals obtained from the processing can be useful not only in evaluating the characteristics of the LCE but also in understanding uplink and downlink signal quality.
An apparatus for processing multidimensional data with strong spatial characteristics, such as raw image data, characterized by a large number of parallel data streams in an ordered array is described. It comprises a large number (e.g., 16,384 in a 128 x 128 array) of parallel processing elements operating simultaneously and independently on single bit slices of a corresponding array of incoming data streams under control of a single set of instructions. Each of the processing elements comprises a bidirectional data bus in communication with a register for storing single bit slices together with a random access memory unit and associated circuitry, including a binary counter/shift register device, for performing logical and arithmetical computations on the bit slices, and an I/O unit for interfacing the bidirectional data bus with the data stream source. The massively parallel processor architecture enables very high speed processing of large amounts of ordered parallel data, including spatial translation by shifting or sliding of bits vertically or horizontally to neighboring processing elements.
Pervaporation, combined with other separation processes, can effectively remove water from fermentation product streams, making it highly suitable for purifying alcohols like 2,3-butanediol (BDO). In this study, a dense poly(vinylidene fluoride) (PVDF) hollow fiber membrane module prototype was fabricated for BDO dehydration, achieving >0.2 LMH total flux and >95% BDO rejection. With a Markov chain Monte Carlo (MCMC) approach, Bayesian inference was used to quantify the uncertainty of the permeance parameters. A membrane cascade model was developed to scale up a process that purifies a preconcentrated BDO feed (70 wt %) to high purity (90 wt %). Through propagation of the uncertainty of the parameters and sensitivity analyses of the process variables, a cascade design was recommended. Despite data and model limitations, the framework enabled a reliable system analysis and economic evaluation, validated through tight confidence intervals in key process metrics, establishing the foundation for future applications of Bayesian methods in membrane-based processes.
Abstract: Water is a critical resource for crewed space exploration missions and reclamation of aqueous waste streams presents the only long-term viable option. Although early Artemis missions are considering water as part of the payload manifest, it would be extremely advantageous if follow-on missions were supplied—either in total or in part—by a reclamation technology that would operate autonomously between missions. An attractive technology is currently under ongoing research at NASA Glenn Research Center (GRC) that employs a Supercritical Water Oxidation (SCWO) process to destroy all hydrocarbons in the waste stream. Testing of an aqueous waste stream simulant, typical of what is generated on the International Space Station (ISS), has shown reductions in Total Organic Carbon (TOC) of greater than 99% with reactor residence times less than 30 s. Recent effort has been directed toward developing a conceptual design based on the current tubular reactor used in the evaluation of the conversion of SCWO. This conceptual design along with the results of recent SCWO conversion experiments will be presented. Recent design enhancements to achieve shorter residence times along with “production simulation” tests will be presented. The diagnostics used in assessing the extent of the waste conversion include a total organic carbon (TOC) analysis, Raman analyses, and measurements of pH, turbidity, and conductivity. Results obtained from the modified reactor configuration will also be compared to those of the Phase I configuration presented in earlier work.
A novel cognitive computing architecture is conceptualized for processing multiple channels of multi-modal sensory data streams simultaneously, and fusing the information in real time to generate intelligent reaction sequences. This unique architecture is capable of assimilating parallel data streams that could be analog, digital, synchronous/asynchronous, and could be programmed to act as a knowledge synthesizer and/or an "intelligent perception" processor. In this architecture, the bio-inspired models of visual pathway and olfactory receptor processing are combined as processing components, to achieve the composite function of "searching for a source of food while avoiding the predator." The architecture is particularly suited for scene analysis from visual data and odorant.
We have investigated the role of biological processes in the C-isotopic dynamics of the aquatic ecosystems in Taylor Valley, Antarctica. This cold desert ecosystem is characterized by the complete lack of vascular plants, and the presence of algal mats in ephemeral streams and perennially ice covered lakes. Streams having abundant algal mats and mosses have very low sigma CO2 concentrations, as well as the most depleted delta C-13 values (-4%). Previous work has shown that algal mats in these streams have delta C-13 values averaging -7.01%. These values are similar to those observed in the algal mats in shallow areas of the lakes in Taylor Valley, where CO2 is thought to be colimiting to growth. These low Sigma CO2 concentrations, and delta C(13) signatures heavier than the algal mats, suggest that CO2 may be colimiting in the streams, as well. Streams with little algal growth, especially the longer ones in Fryxell Basin, have higher Sigma CO2 concentrations and much more enriched isotopic signatures (as high as +8%). In these streams, the dissolution of isotopically enriched, cryogenic CaCO3 is probably the major source of dissolved carbonate. The delta C(13) geochemistry of Antarctic streams is radically different from the geochemistry of more temperate streams, as it is not affected by terrestrially produced, isotopically depleted Sigma CO2. These results have important implications for the understanding of "biogenic" carbonate that might have been produced from aquatic ecosystems in the past on Mars.
This is the final report for the DOE ASCR grant SC-0022260, Data Summarization and Inference at Scale, PI: Alex Pothen, Purdue University. The goal of the project was to solve data-intensive and compute-intensive problems in the physical sciences, engineering, information science, data science, etc. by designing and implementing new algorithms that could work with a subset of the data. The four subgoals were: (a) The solution of problems where the data is too large to be stored in the memory of a computer. In this streaming model of computation, the data arrives as a stream of elements to the computer, each element is processed as it arrives, and a decision is made to discard the data or to store it; only a small subset of the data proportional to the size of the output solution is stored, and when all the data has been streamed, a solution to the problem is computed from the stored subset. (b) The use of machine learning methods to compute solutions to data-intensive problems. The use of GPUs is critical to obtain high performance on machine learning tasks, but their memory sizes are smaller relative to that of CPUs. For large-scale problems, the data is sampled many times, and small samples are used with repetition, for robustness, to compute solutions to inference tasks. This sampling reduces the memory required to solve the problem, but attention is needed to avoid slow convergence to the solutions, and reduced accuracy of inference. We propose submodular optimization, Large Language Models, and physics-informed neural networks to enable GPU computations here. (c) Modeling and visualization of high-dimensional data using interpretable features. Clinical proteomic data sets from immunology for the detection of cancer and other diseases are temporal and high-dimensional, and algorithms for visualizing these data sets using clinically interpretable features are lacking. We propose methods that compute distances based on the optimal transportation problem and graph edit distances to address this problem. We also propose the use of optimal transport-based distances, spatial statistics, and network structure to classify image data sets, We apply these algorithms to electron micrographs of the peripheral nervous system in the digestive tract. (d) The design of data-intensive algorithms on emerging architectures, specifically, noisy, intermediate-scale quantum (NISQ) devices. Quantum computers offer the possibility of exploring large solution spaces due to the principle of superposition, but current quantum computers are limited by few qubits, short coherence times due to noise, poor interconections among the qubits, etc. We propose the use of the divide and conquer paradigm to solve large-scale problems, wherein collections of small subproblems are solved on the quantum devices, and the solutions to the subproblems are integrated into a solution for the original problem on a classical computer.
The scarcity of water resources, the need for beneficial water reuse, and the challenges of wastewater treatment are becoming increasingly pressing in economic, social, and environmental domains. Addressing these concerns requires effective treatment strategies to manage wastewater streams and tackle environmental and economic issues. Furthermore, the recovery of critical minerals from the waste streams associated with energy production holds the promise of offsetting treatment costs and securing local sources of valuable minerals. However, relevant data on these waste streams are dispersed and challenging to locate. The process of ingesting such data into modeling software often involves multiple steps, requiring data restructuring to meet software-input requirements. The non-standardized reporting of water data makes data aggregation and reformatting a time-consuming process. Additionally, essential attributes necessary for modeling water treatment and mineral scale formation are frequently missing. Moreover, data gaps vary depending on the region of interest. Consequently, there is a pressing need for high-quality energy-water composition data that can be easily imported into water chemistry modeling software. To address this need, the National Energy Technology Laboratory has created the National Energy Water Treatment and Speciation (NEWTS) Database and Dashboard—a free online tool catering to community leaders and water researchers. NEWTS facilitates a comprehensive understanding of the composition of energy-related wastewater streams in the United States. The datasets provide detailed concentrations and speciation of major and minor aqueous compounds in energy-related wastewater streams, including power plant leachate, acid mine drainage, brackish water, and oil and gas produced water across the United States. Many of the aqueous species are critical minerals (Li, REEs) in high demand to modernize the world’s energy infrastructure. Many of the datasets also contain volumetric flow-rates needed to model the treatment and reuse scenarios in advanced aqueous chemistry software programs. The NEWTS Database and Dashboard offer public access to hitherto challenging-to-access datasets, presented in a standardized format that is tailored for easy input into aqueous chemistry modeling software. By performing the work needed to transform dispersed, disparate data sources into unified, model-ready datasets, NEWTS serves as an essential resource in advancing water treatment research and sustainable water resource management.
The purpose of this paper was to provide insight into the nature of response selection by reviewing the literature on stimulus-response compatibility (SRC) effects and the psychological refractory period (PRP) effect individually and jointly. The empirical findings and theoretical explanations of SRC effects that have been studied within a single-task context suggest that there are two response-selection routes-automatic activation and intentional translation. In contrast, all major PRP models reviewed in this paper have treated response selection as a single processing stage. In particular, the response-selection bottleneck (RSB) model assumes that the processing of Task 1 and Task 2 comprises two separate streams and that the PRP effect is due to a bottleneck located at response selection. Yet, considerable evidence from studies of SRC in the PRP paradigm shows that the processing of the two tasks is more interactive than is suggested by the RSB model and by most other models of the PRP effect. The major implication drawn from the studies of SRC effects in the PRP context is that response activation is a distinct process from final response selection. Response activation is based on both long-term and short-term task-defined S-R associations and occurs automatically and in parallel for the two tasks. The final response selection is an intentional act required even for highly compatible and practiced tasks and is restricted to processing one task at a time. Investigations of SRC effects and response-selection variables in dual-task contexts should be conducted more systematically because they provide significant insight into the nature of response-selection mechanisms.
An engineering tool for analyzing ejectors in rocket based combined cycle (RBCC) engines has been developed. A key technology for multi-cycle RBCC propulsion systems is the ejector which functions as the compression stage of the ejector ramjet cycle. The THRee STream Ejector Ramjet analysis tool was developed to analyze the complex aerothermodynamic and combustion processes that occur in this device. The formulated model consists of three quasi-one-dimensional streams, one each for the ejector primary flow, the secondary flow, and the mixed region. The model space marches through the mixer, combustor, and nozzle to evaluate the solution along the engine. In its present form, the model is intended for an analysis mode in which the diffusion rates of the primary and secondary into the mixed stream are stipulated. The model offers the ability to analyze the highly two-dimensional ejector flowfield while still benefits from the simplicity and speed of an engineering tool. To validate the developed code, wall static pressure measurements from the Penn-State and NASA-ART RBCC experiments were used to compare with the results generated by the code. The calculated solutions were generally found to have satisfactory agreement with the pressure measurements along the engines, although further modeling effort may be required when a strong shock train is formed at the rocket exhaust. The range of parameters in which the code would generate valid results are presented and discussed.
An engineering tool for analyzing ejectors in rocket based combined cycle (RBCC) engines has been developed. A key technology for multi-cycle RBCC propulsion systems is the ejector which functions as the compression stage of the ejector ramjet cycle. The THRee STream Ejector Ramjet analysis tool was developed to analyze the complex aerothermodynamic and combustion processes that occur in this device. The formulated model consists of three quasi-one-dimensional streams, one each for the ejector primary flow, the secondary flow, and the mixed region. The model space marches through the mixer, combustor, and nozzle to evaluate the solution along the engine. In its present form, the model is intended for an analysis mode in which the diffusion rates of the primary and secondary into the mixed stream are stipulated. The model offers the ability to analyze the highly two-dimensional ejector flowfield while still benefits from the simplicity and speed of an engineering tool. To validate the developed code, wall static pressure measurements from the Penn-State and NASA-ART RBCC experiments were used to compare with the results generated by the code. The calculated solutions were generally found to have satisfactory agreement with the pressure measurements along the engines, although further modeling effort may be required when a strong shock train is formed at the rocket exhaust. The range of parameters in which the code would generate valid results are presented and discussed.
In early 1994, Voyager 2 at 42-43 AU near heliolatitude 10 deg S observed over a period of approximately 100 days a remarkable sequence of quasi-recurrent stream fronts, wherein the background (ambient) speed rose steadily from approximately 450 to approximately 550 km/s while the mean period of the streams decreased from the usual 25 days down to approximately 20 days. A qualitative explanation for this effect can be derived from IMP observations, which show that the amplitude of the stream structure at 1 AU increased monotonically in late 1993, concurrent with major secular evolution in the corona. The reduction in period, then, amounts to a doppler shift due to the progressive overtaking of successively faster streams in the sequence. Attempts to model this process quantitatively with 1-D dynamic simulations falter on three accounts: (1) the reduction in period is overestimated, (2) the simulation predicts many more fronts surviving to 43 AU than are observed by Voyager; (3) the density variations are much too large. It is argued that inclusion of the 3-D geometry in the simulation would resolve most all these shortcomings. Using a series of calculations executed with 1-D, 2-D, and 3-D MHD models of hypothetical tilted-dipole flows, we show that: (1) the radial propagation velocities of 3-D fronts are less than those of 1-D or 2-D fronts, owing to the tilt of (and increased shearing across) the interaction surfaces hence the overtaking rate of successive streams is reduced; (2) in a tilted-dipole geometry, the reverse fronts should largely disappear from the equatorial plane by 43 AU, effectively halving the number of fronts to be observed (see companion paper on predominance of forward fronts at Voyager); and (3) the density enhancements would be much smaller than predicted by a 1-D model.
The SLS rocket was instrumented to collect liftoff environment data during Artemis I launch. The instruments were microphones and pressure transducers. Most data were acceptable for analysis, but required corrections for port resonance, mean signal drift, data system delays, and data spikes. The data were all transmitted via telemetry and in this process some of the measurements experienced unexpectedly long gaps in the data stream. A time validated reconstruction algorithm failed when encountering the long gaps and required use of data from a simpler reconstruction process, with manually inserted data delay corrections. This paper discusses the issues and the corrections that were necessary for the launch data to determine the true physics of the acoustics occurring during launch.
The SLS rocket was instrumented to collect liftoff environment data during Artemis I launch. The instruments were microphones and pressure transducers. Most data were acceptable for analysis, but required corrections for port resonance, mean signal drift, data system delays, and data spikes. The data were all transmitted via telemetry and in this process some of the measurements experienced unexpectedly long gaps in the data stream. A time validated reconstruction algorithm failed when encountering the long gaps and required use of data from a simpler reconstruction process, with manually inserted data delay corrections. This paper discusses the issues and the corrections that were necessary for the launch data to determine the true physics of the acoustics occurring during launch.