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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Systematic Method and Tool for Sustainable Process Synthesis, Designanalysis and Innovation

Computer-aided tools have been successfully developed and used in different segments of the entire process development cycle. For example, there are established tools for chemical process design, simulation, heat exchanger network synthesis and many more. However, one needs an integrated platform to perform process synthesis, design and analysis of chemical processes in a systematic manner. Also, in order to obtain a truly innovative and sustainable solution, it is necessary to search the entire feasible search space of alternatives and select the best process alternative, which is not very easy and will be time consuming. Therefore, it is beneficial to utilize computer-aided methods and tools to enumerate, analyze and determine within the design space, the more sustainable processes. This work highlights the development of a computer aided methodology and corresponding integrated platform for fast, reliable and consistent generation of process flowsheets. As a result, this paper gives an overview of the key concepts and the method is presented along with details of the developed computer-aided tool.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Phenomena-based graph representations and applications to chemical process simulation

Rapid and robust simulation of chemical processes is critical to conduct process design, optimization, techno-economic analysis, and sustainability analysis. Yet, efficiently solving simulation models remains a challenge due to the highly coupled and nonlinear nature of the underlying algebraic equations that capture the physical phenomena taking place in the process (e.g., material and energy conservation, phase equilibrium, reactions). In this work, we show that graph-theoretic representations of the physical phenomena within unit operations can help navigate and decompose equations to systematically identify alternative approaches for fast and robust numerical solutions. Specifically, we present a graph-theoretic abstraction that captures the connectivity between the model variables/equations and use this abstraction to group variables/equations into fundamental phenomena. We show that phenomena-based decomposition of the underlying equations can help decouple nonlinearities and enforce material/energy conservation at the process level to accelerate convergence. The proposed decomposition approach differs from the more traditional sequential modular simulation approach, in which equations are grouped and decomposed by unit operations. We implemented the phenomena-based decomposition in BioSTEAM—an open-source process simulation platform in Python—and demonstrated that this approach can converge a variety of separation process models. Compared to sequential modular simulation, the phenomena-based approach can converge idealized systems faster, but it can be slower for (or even fail to converge) highly coupled and nonideal process systems.

Convergence↗
DOE OSTI2025

Process intensification approach to enhancing heat and mass transfer: Radio frequency (RF) assisted drying of paper and board

Conventional multi-cylinder drying of paper and board typically relies on both conductive drying from steam-heated cylinders and convective drying, where heated air flows over the paper web surface. Conduction primarily contributes to heat transfer, while convection is the main driver of mass transfer. However, conventional drying systems are heavily dependent on steam, usually powered by fossil fuels, and are often energy-inefficient with high levels of waste. Additionally, these surface-driven processes result in a lower percentage of energy absorption compared to the energy supplied, leading to significant energy losses. To improve this long-standing process, an experimental system was developed to investigate a process intensification approach involving the integration of Radio Frequency (RF) heating, a volumetric electromagnetic technology, alongside traditional conduction and convection drying methods. This study also emphasizes the use of sensors to continuously monitor key parameters such as moisture content, supply system temperatures, sample temperatures, air flows, and drying rates in real-time. The effect of RF as an auxiliary energy source in localized environments at varying moisture levels was explored to optimize industrial drying systems, quantify potential improvements, and provide insights for future studies. Experimental results from trials combining RF with convection and with the base case alternating conduction-convection drying processes are presented. It is shown that RF is a viable process intensification approach for paper drying improving the drying rate and energy intensity at higher moisture contents. These findings offer valuable insights for process intensification and contribute to the process development, modeling, and simulation of advanced paper drying techniques.

42 ENGINEERING↗
DOE OSTI2018

Toward supplying food, energy, and water demand: Integrated solar desalination process synthesis with power and hydrogen coproduction

The increase in population coupled with rising per capita income and associated change in consumption habits will put unprecedented stress on food, energy and water (FEW) resources. Sustainable and reliable fresh water supply is central for life and also for all sectors that support our existence. Uncertainty on water security prompted interest in investigation of renewable energy driven desalination processes. One particularly promising option is to produce fresh water from the two most abundant resources on earth: solar energy and seawater. In this study, using Solar Electricity, Water, Food and Chemical (SEWFAC) process synthesis concept, we explore and identify synergistic integration alternatives of multi stage flash desalination, solar thermal power, and hydrogen production processes. The promising options have been analyzed by detailed process simulation and optimization using an integrated Aspen Plus and MATLAB modeling environment. The proposed process designs can meet the water and electricity demand with rather high conversion efficiencies. Furthermore, integration of solar hydrogen production and hydrogen-fired power plant can enable continuous production of fresh water and electricity in solar-rich water-poor regions. In addition to other metrics, we have evaluated the performance of the desalination process from power point of view with a new metric, Electricity Equivalent Water (EEW) to demonstrate the marginal energy penalty of desalination. Integration of thermal desalination processes with electricity and hydrogen production is a synergistic alliance and can play a pivotal role in approaching FEW nexus.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Water Processing for Isotope Recovery Using Porous Zero Valent Iron

Reduction-oxidation cycles of metals can be harnessed to create a reusable tritiated water processing system. The concept is straightforward; a tritium-contaminated steam passes over a hot metal bed converting the metal to a metal oxide and liberating hydrogen isotopes for further processing and isotope separation. The bed is regenerated by converting the metal oxide back to a bare metal using protium gas, creating a clean water stream. Free oxygen is not produced during the cyclical process, making it safe for use in a hydrogen processing facility, and the only by-product is detritiated water. Porous zero valent iron (p-ZVI) has been identified as an ideal candidate material for this process due to its low cost, unique morphology, and favorable thermodynamics. Therefore, investigations of p-ZVI were conducted to better understand how a bed composed of such material would behave in a tritium processing facility. The thermal and physical properties were assessed, along with cycling and isotope effects. The results indicate that p-ZVI beds could serve as a low-cost, reusable system for the treatment of water in tritium processing facilities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Recursive Use of the Short-Time Fast Fourier Transform for Signature Analysis in Continuous Processes

Although a nuclear reactor is a hostile environment for sensing and electrical communications, the reactor core is amenable to acoustic communication. An acoustic measurement infrastructure (AMI) has been installed in the Advanced Test Reactor (ATR) to record acoustic signals that can capture its different operating regimes. AMI uses coolant pumps as continuous signal sources, coolant and structural components as transmission lines, and accelerometers to capture system motion. A recursive signal processing technique based on the short-time fast Fourier transform (STFFT) for continuous processes provides unique signatures for diagnostic and prognostic analyses from the system motion data. Here this article presents a recursive STFFT methodology that processes acoustic signals from continuous industrial processes. The article first discusses the initial STFFT use with simulated data to elucidate the basic principles necessary to understand and interpret the STFFT results from actual pump vibration data. Each repetitive use of the STFFT on pump vibration data using the results from the prior STFFT processing will generate additional complimentary time-frequency-based signatures. These signatures are generated by the coolant pumps operating under different process conditions. After each use of the STFFT, the resulting signatures provide exemplary examples of the diversity and intuitive nature of recursively using the STFFT. This article focuses on recursively using the STFFT to provide numerous complimentary and diverse signatures that will ultimately be inputs for machine learning algorithms that provide predictive data analytics. The intuitive nature of the information and signatures from recursive STFFT processing will also bring intuitive interpretation capabilities to machine learning and predictive data analytic techniques.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

In-Situ Calibrated Digital Process Twin Models for Resource Efficient Manufacturing

The chief objective of manufacturing process improvement efforts is to significantly minimize process resources such as time, cost, waste, and consumed energy while improving product quality and process productivity. This paper presents a novel physics-informed optimization approach based on artificial intelligence (AI) to generate digital process twins (DPTs). The utility of the DPT approach is demonstrated in the case of finish machining of aerospace components made from gamma titanium aluminide alloy (γ-TiAl). This particular component has been plagued with persistent quality defects, including surface and sub-surface cracks, which adversely affect resource efficiency. Previous process improvement efforts have been restricted to anecdotal post-mortem investigation and empirical modeling, which fail to address the fundamental issue of how and when cracks occur during cutting. In this work, the integration of in-situ process characterization with modular physics-based models is presented, and machine learning algorithms are used to create a DPT capable of reducing environmental and energy impacts while significantly increasing yield and profitability. Based on the preliminary results presented here, we report an improvement in the overall embodied energy efficiency of over 84%, 93% in process queuing time, 2% in scrap cost, and 93% in queuing cost has been realized for γ-TiAl machining using our novel approach.

42 ENGINEERING↗
DOE OSTI2023

Modeling Tool Development and Validation for Solar Industry Process Heat Using Particle Thermal Energy Storage

U.S. industry sectors used 26.2 quadrillion Btu and accounted for 33% of total energy consumption in 2021 according to the Energy Information Agency. Industrial process heat accounts for 70% of industrial energy use with application temperatures ranging from 60 degrees -1100 degrees C. Industry processes, heavily relying on fossil fuels of cheap coal or natural gas, differ widely in operating conditions and load requirements which makes them difficult to standardize and imposes great challenges in decarbonization. Industry processes require reliable energy supply and vary widely in temperature ranges. Storing energy from renewable sources is necessary to improve reliability and to mitigate renewable intermittency when replacing carbon fuel-based heat supplies to achieve energy savings and reduce emissions. To this end, we have developed a particle-based thermal energy storage (TES) technology using low-cost and highly stable silica sand as a storage medium. The economic and performance-based analysis is key for renewable energy sources to reliably supply industry process heat and ultimately displace fossil fuels for decarbonization. The diversified industrial processes need case-by-case analysis and design. Therefore, an adaptive modeling tool is key for renewable power with energy storage to meet industry demands. Thus, a modeling tool to simulate a solar industry process heat system using the particle TES has been developed using the object-oriented equation-based language Modelica and the commercial platform of Modelon Impact. The Modelica-based software tool provides a general simulation environment for the design of reliable solar energy sources integrated with TES for various industrial process applications at different temperatures for economic competence with fossil fuels such as coal and natural gases. It uses both customized and standard component modeling modules in Modelon libraries for the flexibility to be adapted to a specific energy demand application. The particle TES system establishes a uniform energy supply platform with an efficient heat exchanger and particle thermal energy reservoir integrated with renewable powers. The particle TES system can provide a wide temperature range and can have a large storage temperature difference that increases storage energy density; therefore, it can be an adaptable energy storage system integrated with renewable power to supply 24/7 heat for industry decarbonization.

concentrated solar thermal↗
DOE OSTI2018

The Effect of Flocculent, Dispersants, and Binder on Wet-laid Process for Recycled Glass Fiber/PA6 Composite

The papermaking industry has been using the wet-laid process to suspend paper pulp-derived fibers in water and drain the solution through a forming mesh. This process has recently been adopted to produce non-woven, wet-laid fiber-reinforced polymer matrix composite mats. The mats can be postmolded into different complex shapes using compression molding or related processes. The objective of this study was to produce composite panels from wet-laid mats and observe the effect of chemicals used during the process on the mechanical and thermal characteristics of the resulting composite. Two sets of mats were processed using recycled glass fiber with Polyamide 6 (PA6). Flocculent, dispersant and binder (poly(vinyl alcohol) (PVOH)) were added to one of the mats, and the second mat was processed without these chemicals. The addition of these chemicals enhanced the fiber distribution and reduced processing defects in the mats. This was reflected in the mechanical properties of the final product. It was noticed that the flocculent, dispersant and binder volatilized during the compression molding step. Furthermore, the additives were found not to affect the thermal properties of the consolidated part.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Narrow-Band Least-Squares Infrasound Array Processing

Infrasound data from arrays can be used to detect, locate, and quantify a variety of natural and anthropogenic sources from local to remote distances. However, many array processing methods use a single broad frequency range to process the data, which can lead to signals of interest being missed due to the choice of frequency limits or simultaneous clutter sources. In this work, we introduce a new open-source Python code that processes infrasound array data in multiple sequential narrow frequency bands using the least-squares approach. We test our algorithm on a few examples of natural sources (volcanic eruptions, mass movements, and bolides) for a variety of array configurations. Our method reduces the need to choose frequency limits for processing, which may result in missed signals, and it is parallelized to decrease the computational burden. Improvements of our narrow-band least-squares algorithm over broad-band least-squares processing include the ability to distinguish between multiple simultaneous sources if distinct in their frequency content (e.g., microbarom or surf vs. volcanic eruption), the ability to track changes in frequency content of a signal through time, and a decreased need to fine-tune frequency limits for processing. We incorporate a measure of planarity of the wavefield across the array (sigma tau, στ) as well as the ability to utilize the robust least trimmed squares algorithm to improve signal processing and insight into array performance. Our implementation allows for more detailed characterization of infrasound signals recorded at arrays that can improve monitoring and enhance research capabilities.

58 GEOSCIENCES↗
DOE OSTI2020

Characterization and CST Batch Contact Equilibrium Testing of Modified Tank 9H Process Supernate Samples in Support of TCCR

The Tank Closure Cesium Removal (TCCR) system uses ion exchange columns filled with crystalline silicotitanate (CST) media to process radioactive waste solutions for the removal of ¹³⁷Cs. TCCR currently focuses on dissolving Savannah River Site (SRS) radioactive tank waste (primarily sodium saltcake solids) within Tank 10H followed by at-tank ion exchange column treatment. Two supernate batches from Tank 10H have been processed through the TCCR unit and processing of a third batch is expected soon. After processing of this supernate batch, plans are to replace the CST columns and process dissolved salt solution from Tank 9H through Tank 10H and then through the new CST columns installed in the TCCR unit. The new columns are expected to contain either a media similar to an archived CST batch (IE-911) or the R9120-B CST media used in the current TCCR columns (the two materials are fundamentally the same; just different specifications, product names, and preconditioning steps). Samples of Tank 9H dissolved saltcake were received at the Savannah River National Laboratory (SRNL) and characterized. The Tank 9H supernate contained a high sodium concentration (~9.6 M Na⁺) and will require dilution to near 6 M [Na⁺] prior to processing through the TCCR unit. The cesium concentration in Tank 9H is currently significantly higher than was observed with Tank 10H. Three dilutions of the Tank 9H supernate were conducted to mimic possible dilutions that could be conducted in the tank farm prior to TCCR processing using inhibited water, sodium hydroxide, and sodium nitrate solutions. Dilution #1 was prepared by diluting the Tank 9H supernate by a factor of 1.6 with inhibited water, Dilution #2 was prepared by diluting the Tank 9H supernate by a factor of 3.7 with a mixed sodium hydroxide/sodium nitrate diluent, and Dilution #3 was prepared by also diluting by a factor of 3.7 but with sodium hydroxide only. All three dilutions have similar Na⁺ concentrations (~6 M), but Dilutions #2 and #3 contain significantly less cesium. Major and key minor components of the diluted Tank 9H supernate samples are provided in Table ES-1. Batch contact equilibrium tests were conducted with the Tank 9H dilutions and the two different CST media batches being considered for use in the new TCCR columns. Results are summarized in Table ES-2 and compared to ZAM model predictions. The highest cesium distribution coefficient and percent removal were observed with Dilution #3. IE-911 CST (an archived CST media batch) was more effective at removing cesium than the more recently prepared R9120-B CST media, though both media samples removed >88% of the cesium and the differences may not be statistically different considering the overall uncertainty. Based on the results, maximum cesium loadings were calculated for each CST media type and Tank 9H dilution. In general, maximum cesium loadings from dilutions of this supernate batch are quite high (approaching 0.1 mmol total Cs⁺/g CST for Dilution #1). The highest calculated maximum ¹³⁷Cs loading for the Tank 9H dilutions using the ZAM model with input of the tank compositions and batch contact results was 207 Ci/kg CST (Dilution #1 with IE-911 CST). In all cases, higher maximum cesium loading values were predicted for IE-911 CST versus R9120-B, although the differences varied considerably between the dilutions. The maximum loading value for IE-911 CST with Tank 9H Dilution #1 was only 7% higher than the maximum loading for R9120-B. The maximum loading value for IE-911 CST with Dilution #3 was 24% higher than the maximum loading for R9120-B. Dilution #2 was intermediate between these values. Note that these maximum loading values are the theoretical calculated values, and actual operating conditions will cause differences. A CST binder dilution (correction) factor near 0.7 (relative to pure powder CST) was required for each batch contact test with IE-911 engineered CST using the three Tank 9H dilutions. Correction factors calculated for R9120-B CST ranged from 0.56 to 0.66 for the three dilutions. Following the batch contact tests, the CST samples were isolated from the Tank 9H solution, washed, dried, and digested in acid following established procedures. The analysis results are provided in Table ES-3. Total cesium loading values determined by CST digestion were similar to the calculated loading values based on solution analysis (Table ES-2) for all samples. In addition, the CST was observed to load calcium (R9120-B sample only), iron, strontium, lead, uranium, and plutonium after contact with the waste supernate, as has been observed previously.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Shear Assisted Processing and Extrusion (ShAPE) of Aluminum Alloy 7075, 2024, and Al-12.4TM

The most common aluminum alloys utilized in the aerospace industry are 7075 and 2024 due to their high strength-to-weight ratio compared to advanced high strength steels and other aluminum alloys. Despite excellent performance, these aluminum alloys have seen limited use outside of the aerospace industry due in part to high cost. If high-performance aluminum extrusions could be made more cost effectively by eliminating energy intensive process steps typical of conventional extrusion, then numerous opportunities exist for more widespread adoption. A key reason for the high cost of 7075 and 2024 extrusions (25-75% higher than 6061) is their slow extrusion speed. 7075 and 2024 are limited to 2 m/min and 3.5 m/min respectively, in contrast to 6061 which can be extruded at 20–80 m/min. In addition to slow speed, aluminum alloys require numerous thermal treatments throughout the extrusion process including homogenization and pre-heating prior to extrusion, and solution heat treating and artificial aging after extrusion. Each of these steps contribute to the total energy consumed during manufacturing of extruded components. This project investigates the use of ShAPE to improve extrusion speed and reduce, or even eliminate, the typical thermal treatments for high strength aluminum alloys, all while improving material performance. The overarching goal of this project was to demonstrate that Shear Assisted Processing and Extrusion (ShAPE) can manufacture high-performance aluminum alloy tubing with lower manufacturing energy and improved mechanical properties compared to conventional extrusion. Unlike conventional extrusion where the billet is rammed against a stationary die using a strictly linear motion, the ShAPE process superimposes a rotational shear force by spinning the die while the billet is plunged. Compared to conventional linear extrusion, the ShAPE process imparts significantly more strain into the feedstock material, which enables the formation of novel microstructures. These microstructures manifest an array of property and process improvements for extrusion of high-performance aluminum alloys. The following accomplishments were achieved for this project: Extrusion of 7075 at 12.2 meters/min compared to 2 meters/min for conventional extrusion; Elimination of 7075 billet homogenization (430 °C for 20 hours) which is required prior to conventional extrusion; Elimination of 7075 billet pre-heating (400 °C for 1 hour) in a separate furnace which is required prior to conventional extrusion; Achieved 7075-T6with yield strength = 595 MPa, ultimate tensile strength = 531MPa, and elongation = 17.4% for extrusions made from unhomogenized billets. Exceeds the ASTM and ASM standard, and typical industry values; Achieved 7075-T5 (i.e., no solution heat treatment) with yield strength = 588 MPa, ultimate tensile strength = 535 MPa, and elongation = 14.8% for extrusions made from homogenized billets; Extrusion of 2024 at 7.4 meters/min compared to 3.5 meters/min for conventional extrusion; Achieved 2024-T8510 yield strength = 522 MPa, ultimate strength = 510MPa, and elongation = 7.1% for extrusions made from wrought billets. Exceeds the ASTM and ASM standard, and typical industry values; Extrusion of Al-12.4TM high-performance aluminum powder directly into tubing, in a single step, which eliminates process steps typical of powder metallurgy extrusion.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The Role of Process-Directing Agents on Enamel Lesion Remineralization: Fluoride Boosters

The aim of this study was to investigate the effects of two process-directing agents (polyaspartic acid and osteopontin) used in a polymer-induced liquid-precursor (PILP) process on the remineralization of bacteria-induced enamel demineralization. Enamel demineralization lesions (depths of about 180–200 µm) were created and exposed to Streptococcus mutans, cultured with a 10% sucrose solution for 21 days, and remineralized using a PILP process (pH = 7.4, 14 days) with a calcium phosphate solution containing either polyaspartic acid or osteopontin in the presence or absence of fluoride (0.5 ppm). The specimens were examined under scanning electron microscopy. The fluoride was successfully incorporated into the PILP remineralization process for both polyaspartic acid and osteopontin. When the fluoride was added to the PILP remineralization solution, there was more uniform remineralization throughout the lesion than with either polyaspartic acid or osteopontin alone. However, in the absence of these process-directing agents, fluoride alone showed less remineralization with the formation of a predominantly surface-only layer. The PILP remineralization process relies on the ability of process-directing agents to stabilize calcium phosphate ions and holds promise for enamel lesion remineralization, and these agents, in the presence of fluoride, seem to play an important role as a booster or supplement in the continuation of remineralization by reducing the mineral gains at the surface layer.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Selecting Post-Processing Schemes for Accurate Detection of Small Objects in Low-Resolution Wide-Area Aerial Imagery

In low-resolution wide-area aerial imagery, object detection algorithms are categorized as feature extraction and machine learning approaches, where the former often requires a post-processing scheme to reduce false detections and the latter demands multi-stage learning followed by post-processing. In this paper, we present an approach on how to select post-processing schemes for aerial object detection. We evaluated combinations of each of ten vehicle detection algorithms with any of seven post-processing schemes, where the best three schemes for each algorithm were determined using average F-score metric. The performance improvement is quantified using basic information retrieval metrics as well as the classification of events, activities and relationships (CLEAR) metrics. We also implemented a two-stage learning algorithm using a hundred-layer densely connected convolutional neural network for small object detection and evaluated its degree of improvement when combined with the various post-processing schemes. The highest average F-scores after post-processing are 0.902, 0.704 and 0.891 for the Tucson, Phoenix and online VEDAI datasets, respectively. The combined results prove that our enhanced three-stage post-processing scheme achieves a mean average precision (mAP) of 63.9% for feature extraction methods and 82.8% for the machine learning approach.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Gamma Rays as a Signature of r -process Producing Supernovae: Remnants and Future Galactic Explosions

We consider the question of whether core-collapse supernovae (CCSNe) can produce rapid neutron capture process (r-process) elements and how future MeV gamma-ray observations could address this. Rare types of CCSNe characterized by substantial magnetic fields and rotation, known as magnetorotational supernovae (MR-SNe), are theoretically predicted to produce these elements, although direct observational evidence is lacking. We suggest that this critical question be addressed through the study of some of the 11 CCSN remnants located within 10 kpc, as well as through the detection of gamma-ray emission from a future Galactic supernova. We use a two-dimensional MR-SN model to estimate the expected gamma flux stemming from nuclear decays in the range of a few tens of keV to a few MeV. Our results indicate that an observation of 126 Sn ( 126 Sb) in a remnant stands out as a signature of an r-process-producing supernova. Since the neutron-rich conditions that lead to the production of the r-process could also enhance the production of 60 Fe, the detection of substantial 60 Fe ( 60 Co) would be indicative of favorable conditions for the r-process. In the case of a future supernova explosion, when the evolution of the spectrum is studied over 10 days to a few years, a rich picture emerges. At various epochs, the second peak r-process isotopes such as 125 Sn, 131 I, 132 Te, 132 I, and 140 La produce signals that are not obscured by the gamma emission from explosive burning products and electron–positron annihilation. The weak r-process isotopes 95 Nb, 103 Ru, and 106 Rh also have periods of prominence.

Gamma-rays↗
NASA NTRSDate not supplied

High Temperature Material Property Data and Challenges to Thermal Process Model Predictions and In-Situ/Ex-Situ Measurements for Metallic Additive Manufacturing

Understanding and predicting performance properties of parts produced by metallic additive manufacturing has improved significantly over the past decade; however, difficult to measure material properties and process outcomes continue to be challenges. The qualification or certification of aerospace parts require extensive measures to quantify variable part properties in order to buy down the risk of component failure. The variability, inherent to the additive manufacturing, process adds unwanted uncertainty in the production of load critical structural components. Process modeling has proven valuable in providing predictions and context for understanding outcomes of the additive manufacturing process; however, these physically informed process models require material properties at temperatures that are difficult to measure and rarely available. Further, calibrating or validating such models is difficult because the process itself is challenging to measure. This talk will explore some of the challenges resulting from difficult to acquire input data by relating thermal process model predictions to in-situ and ex-situ optical microscopy measurements.

Process Model↗
NASA NTRSDate not supplied

Navigation Doppler Lidar Signal Processing Architecture and Algorithms

A coherent Doppler lidar has been developed to address the need for a high-performance, compact, and cost-effective velocity and altitude sensor onboard landing vehicles. One of the core subsystems within NDL is its signal processing architecture. The primary function of this subsystem is to digitize the analog output of the homodyned signal received from the photo-diode associated with each telescope, process this signal in the frequency domain, and then turn this information into velocity and range measurements. A secondary function of this subsystem is to setup and control the internal components within NDL and to enable the instrument to interface with external systems by receiving commands, sending telemetry, and synchronizing its measurements with external clocks and pulses. This paper will give an overview of the signal processing architecture within NDL. This will include a discussion on its fundamental processing components and the core signal processing algorithms. Command, telemetry and internal component controls will also be discussed as will how the signal processing architecture has also evolved over the years of development. We will discuss provisions for robust operation including Triple-Mode Redundancy (TMR) within NDL’s Field Programmable Gate Array (FPGA) and storage elements, a fault-tolerant boot process, and Error Detection and Correction (EDAC) on the Static Random-Access Memories (SRAMs). Finally, we conclude this paper with how this architecture could continue to evolve.

Doppler Lidar↗
DOE OSTI2018

Air Pollutant Emissions and Regulatory Implications of a Biorefinery Co-Processing Bio-Oil in a Petroleum Refinery: Preprint

Pyrolysis oil, often referred to as bio-oil when derived from biomass through a fast pyrolysis process, has attracted considerable attention because of the high carbonaceous matter and high heating value compared to the original biomass. Pyrolysis oil provides a viable link between the agriculture/forestry and (petro-) chemical industry. Utilizing existing fossil fuel infrastructure by introducing bio-oil in petroleum refineries to produce renewable hydrocarbon fuels (i.e., repurposing existing assets) is appealing due to its relatively low capital requirement. Our analysis examined the air pollutant emissions for a biorefinery utilizing an ex situ catalytic fast pyrolysis process to produce raw bio-oil, with a design capacity of 2,000 dry metric tons of biomass per day. Such a biorefinery is capable of providing sufficient bio-oil to a 4,200 barrels per day capacity of fluidized catalytic cracking unit if the bio-oil is co-processed at 5% (by volume) feed rate. This research is focused on understanding the potential air pollutant regulatory and permitting implications for a refinery co-processing 5% bio-oil with 95% vacuum gas oil in a fluidized catalytic cracking unit for two scenarios: the first case assumes that an ex situ biorefinery is collocated with a petroleum refinery, and the second one assumes that a petroleum refinery will receive bio-oil from a stand-alone biorefinery. We estimated the potential-to-emit values for 4 biorefinery and FCC sizes and assessed technically feasible emission control options that could help to avoid being subject to prevention of significant deterioration requirements due to petroleum refinery modifications to co-process bio-oil. This research fills gaps and overcomes barriers related to air permitting requirements for co-processing bio-oil in existing refineries for various stakeholders. The insights gained from this analysis can facilitate decision making and help expedite permitting processes for petroleum refineries, which seek opportunities to produce lower carbon fuels in their existing infrastructure.

09 BIOMASS FUELS↗