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At least 487 records · Page 27

Precision Casting via Advanced Simulation and Manufacturing

A two-year program was conducted to develop and commercially implement selected casting manufacturing technologies to enable significant reductions in the costs of castings, increase the complexity and dimensional accuracy of castings, and reduce the development times for delivery of high quality castings. The industry-led R&D project was cost shared with NASA's Aerospace Industry Technology Program (AITP). The Rocketdyne Division of Boeing North American, Inc. served as the team lead with participation from Lockheed Martin, Ford Motor Company, Howmet Corporation, PCC Airfoils, General Electric, UES, Inc., University of Alabama, Auburn University, Robinson, Inc., Aracor, and NASA-LeRC. The technical effort was organized into four distinct tasks. The accomplishments reported herein. Task 1.0 developed advanced simulation technology for core molding. Ford headed up this task. On this program, a specialized core machine was designed and built. Task 2.0 focused on intelligent process control for precision core molding. Howmet led this effort. The primary focus of these experimental efforts was to characterize the process parameters that have a strong impact on dimensional control issues of injection molded cores during their fabrication. Task 3.0 developed and applied rapid prototyping to produce near net shape castings. Rocketdyne was responsible for this task. CAD files were generated using reverse engineering, rapid prototype patterns were fabricated using SLS and SLA, and castings produced and evaluated. Task 4.0 was aimed at developing technology transfer. Rocketdyne coordinated this task. Casting related technology, explored and evaluated in the first three tasks of this program, was implemented into manufacturing processes.

Source record↗

MIKA: Manager for Intelligent Knowledge Access Toolkit for Engineering Knowledge Discovery and Information Retrieval

Repositories of safety reports are often underutilized and only analyzed manually by trained experts, despite safety management systems requiring reports. These collections of documents contain a wealth of information from past projects and operations that could improve system safety and design. Advances in natural language processing techniques have improved information extraction and retrieval in consumer technology, biomedicine, and finance, for instance, but have not been applied to engineering documents on the same scale. To this end, the Manager for Intelligent Knowledge Access (MIKA) open-source toolkit has been developed for rapid knowledge discovery and information retrieval in safety engineering applications. The MIKA toolkit uses state-of-the-art natural language processing algorithms and allows a user to apply these methods to their own dataset. This paper describes the MIKA toolkit and its two primary capabilities, knowledge discovery and information retrieval, and demonstrates the toolkit via a case study on National Transportation Safety Board (NTSB) reports.

Machine Learning↗

MIKA: Manager for Intelligent Knowledge Access Toolkit for Engineering Knowledge Discovery and Information Retrieval

Repositories of safety reports are often underutilized and only analyzed manually by trained experts, despite safety management systems requiring reports. These collections of documents contain a wealth of information from past projects and operations that could improve system safety and design. Advances in natural language processing techniques have improved information extraction and retrieval in consumer technology, biomedicine, and finance, for instance, but have not been applied to engineering documents on the same scale. To this end, the Manager for Intelligent Knowledge Access (MIKA) open-source toolkit has been developed for rapid knowledge discovery and information retrieval in safety engineering applications. The MIKA toolkit uses state-of-the-art natural language processing algorithms and allows a user to apply these methods to their own dataset. This paper describes the MIKA toolkit and its two primary capabilities, knowledge discovery and information retrieval, and demonstrates the toolkit via a case study on National Transportation Safety Board (NTSB) reports.

Systems Engineering↗

End-To-End Uncertainty Quantification with Analytical Derivatives for Design Under Uncertainty

Uncertainty quantification (UQ) is a rapidly growing and evolving discipline, especially within the aerospace community. Performing analysis with UQ can provide decision makers with a wealth of information about a candidate design. However, the value of UQ is fully realized when the information gained during UQ analysis is leveraged in a feedback loop of a design optimization process, often referred to as design under uncertainty. Although design under uncertainty can be a powerful risk mitigation technique, there are a number of roadblocks that prevent its implementation. Two primary factors are computational costs and added complexity of the analysis. High fidelity simulations on the order tens of uncertain variables quickly become computationally infeasible. Also, implementing UQ into an existing multidisciplinary design and optimization (MDO) process often requires extensive knowledge of the UQ methods and careful treatment of the problem formulation. The objective of this work is to address these two primary roadblocks and enable practitioners to efficiently perform design under uncertainty with limited knowledge of the UQ discipline. Methods outlined in this paper demonstrate MDO incorporating UQ into the design process, leveraging an analytic derivative tool chain through the entire optimization. The proposed approach leverages machine learning techniques to generate a differentiable confidence interval output from polynomial chaos models. This technique, coupled with the incorporation of analytical derivatives through the Polynomial Chaos Expansion (PCE) process, eliminates the need to estimate derivatives which are usually obtained from finite difference, complex step, or similar methods. Developing a differentiable confidence interval allows mixed uncertainty problems (both epistemic and aleatory) to be modeled. Without such modeling, these problems cannot accurately predict objective functions containing statistical quantities such as mean and variance. The addition of analytic derivatives to a polynomial chaos-based UQ method decreases the computational costs of performing design under uncertainty by orders of magnitude in comparison with methods such as complex step. The method and codes developed are modular in nature and are a drop-in solution for design under uncertainty within existing MDO problems. A low-fidelity analytical multidisciplinary optimization under uncertainty for a wing design in OpenMDAO is detailed in this paper. This demonstration case will include both objective functions and constraints which are influenced by uncertain parameters.

Ben D Phillips↗

End-To-End Uncertainty Quantification with Analytical Derivatives for Design Under Uncertainty

Uncertainty quantification (UQ) is a rapidly growing and evolving discipline, especially within the aerospace community. Performing analysis with UQ can provide decision makers with a wealth of information about a candidate design. However, the value of UQ is fully realized when the information gained during UQ analysis is leveraged in a feedback loop of a design optimization process, often referred to as design under uncertainty. Although design under uncertainty can be a powerful risk mitigation technique, there are a number of roadblocks that prevent its implementation. Two primary factors are computational costs and added complexity of the analysis. High fidelity simulations on the order tens of uncertain variables quickly become computationally infeasible. Also, implementing UQ into an existing multidisciplinary design and optimization (MDO) process often requires extensive knowledge of the UQ methods and careful treatment of the problem formulation. The objective of this work is to address these two primary roadblocks and enable practitioners to efficiently perform design under uncertainty with limited knowledge of the UQ discipline. Methods outlined in this paper demonstrate MDO incorporating UQ into the design process, leveraging an analytic derivative tool chain through the entire optimization. The proposed approach leverages machine learning techniques to generate a differentiable confidence interval output from polynomial chaos models. This technique, coupled with the incorporation of analytical derivatives through the Polynomial Chaos Expansion (PCE) process, eliminates the need to estimate derivatives which are usually obtained from finite difference, complex step, or similar methods. Developing a differentiable confidence interval allows mixed uncertainty problems (both epistemic and aleatory) to be modeled. Without such modeling, these problems cannot accurately predict objective functions containing statistical quantities such as mean and variance. The addition of analytic derivatives to a polynomial chaos-based UQ method decreases the computational costs of performing design under uncertainty by orders of magnitude in comparison with methods such as complex step. The method and codes developed are modular in nature and are a drop-in solution for design under uncertainty within existing MDO problems. A low-fidelity analytical multidisciplinary optimization under uncertainty for a wing design in OpenMDAO is detailed in this paper. This demonstration case will include both objective functions and constraints which are influenced by uncertain parameters.

Ben Phillips↗

Biogeochemistry of DMS in Surface Waters

Dimethylsulfide (DMS) is important in influencing the formation of aerosols in the troposphere over large areas of the world's oceans. Understanding the dynamics of aerosols is important to understanding the earth's radiation balance. In evaluating the factors controlling DMS in the troposphere it is vital to understand the dynamics of DMS in the surface ocean. The biogeochemical processes controlling DMS concentration in seawater are myriad; modeling and theoretical estimation are problematic. At the beginning of this project we believed that we were on the verge of simplifying the ship-track measurement of DMS, and we proposed to deploy such a system to develop a database relating high frequency DMS measurements to biological and physicochemical and optical properties of surface water that can be quantified by remote sensing techniques. We designed a system to measure DMS concomitantly with other basic chemical and biological data in a flow-through system. The project was collaborative between Woods Hole Oceanographic Institution (WHOI) and Bermuda Biological Station for Research (BBSR). The project on which we are reporting was budgeted for only one year with a one year no-cost extension. At WHOI our effort was directed towards designing traps which would be used to concentrate DMS from seawater and allow storage for subsequent analysis. At that time, GC systems were too large for easy long-term deployment on a research vessel like R/V Weatherbird, so we focused on simplifying the shipboard sampling procedure. Initial studies of sample recovery with high levels of DMS suggested that Carboxen 1000, a relatively new carbon molecular sieve, could be used as a stable storage medium. The affinity of Carboxen for DMS is several orders of magnitude higher than gold wool (another adsorbent used for DMS collection) on a weight or volume basis. Furthermore, Carboxen's affinity for DMS is also far less susceptible to humidity than gold wool. Unfortunately, further experiments with low level DMS indicated that recovery of DMS after storage was not quantitative. The material has proven to be completely acceptable for short term storage and has been incorporated into a micro-GC system. Since working on this project, we have collaborated with RVM Scientific in Santa Barbara in the design and construction of small portable micro-GC's that will make feasible at-sea measurement in moving ships, making rapid gas analysis and quantification feasible in a ship-track mode. Throughout this period at both WHOI and BBSR, we continued to analyze field data to understand that patterns of time and space variability in DMS and the processes that govern it. These insights will be crucial to determining the specifications for our automated sampling program. The data from this, the longest continuous sampling program for ocean DMS, provided insights into year to year and short-term variability.

Dacey, J. W. H.↗

From Earth to Space: Application of Biological Treatment for the Removal of Ammonia from Water

Managing ammonia is often a challenge in both drinking water and wastewater treatment facilities. Ammonia is unregulated in drinking water, but its presence may result in numerous water quality issues in the distribution system such as loss of residual disinfectant, nitrification, and corrosion. Ammonia concentrations need to be managed in wastewater effluent to sustain the health of receiving water bodies. Biological treatment involves the microbiological oxidation of ammonia to nitrate through a two‐step process. While nitrification is common in the environment, and nitrifying bacteria can grow rapidly on filtration media, appropriate conditions, such as the presence of dissolved oxygen and required nutrients, need to be established. This presentation will highlight results from two ongoing research programs - one at NASA's Johnson Space Center, and the other at a drinking water facility in California. Both programs are designed to demonstrate nitrification through biological treatment. The objective of NASA's research is to be able to recycle wastewater to potable water for spaceflight mission. To this end, a biological water processor (BWP) has been integrated with a forward osmosis secondary treatment system (FOST). Bacteria mineralize organic carbon to carbon dioxide as well as ammonia‐nitrogen present in the wastewater to nitrogen gas, through a combination of nitrification and denitrification. The effluent from the BWP system is low in organic contaminants, but high in total dissolved solids. The FOST system, integrated downstream of the BWP, removes dissolved solids through a combination of concentration‐driven forward osmosis and pressure driven reverse osmosis. The integrated system testing planned for this year is expected to produce water that requires only a polishing step to meet potable water requirements for spaceflight. The pilot study in California is being conducted on Golden State Water Company's Yukon wellsthat have hydrogen sulfide odor, color, total organic carbon, bromide, iron and manganese in addition to ammonia. A treatment evaluation, conducted in 2011, recommended the testing of biological oxidation filtration for the removal of ammonia and production of biologically stable water. A 8‐month pilot testing program was conducted to develop and optimize key design and operational variables. Steadystate operational data was collected to demonstrate long‐term performance and inform California Department of Public Health permitting of the full‐scale process. As ammonia continues to present challenges to water and wastewater systems, innovative strategies such as biological treatment can be applied to successfully manage it. This presentation will discuss application of cutting‐age research being conducted by NASA that will bridge existing information gaps, and benefit municipal utilities.

Ghosh, Amlan↗

From Earth to Space: Application of Biological Treatment for the Removal of Ammonia from Water

Managing ammonia is often a challenge in both drinking water and wastewater treatment facilities. Ammonia is unregulated in drinking water, but its presence may result in numerous water quality issues in the distribution system such as loss of residual disinfectant, nitrification, and corrosion. Ammonia concentrations need to be managed in wastewater effluent to sustain the health of receiving water bodies. Biological treatment involves the microbiological oxidation of ammonia to nitrate through a two‐step process. While nitrification is common in the environment, and nitrifying bacteria can grow rapidly on filtration media, appropriate conditions, such as the presence of dissolved oxygen and required nutrients, need to be established. This presentation will highlight results from two ongoing research programs - one at NASA's Johnson Space Center, and the other at a drinking water facility in California. Both programs are designed to demonstrate nitrification through biological treatment. The objective of NASA's research is to be able to recycle wastewater to potable water for spaceflight missions. To this end, a biological water processor (BWP) has been integrated with a forward osmosis secondary treatment system (FOST). Bacteria mineralize organic carbon to carbon dioxide as well as ammonia‐nitrogen present in the wastewater to nitrogen gas, through a combination of nitrification and denitrification. The effluent from the BWP system is low in organic contaminants, but high in total dissolved solids. The FOST system, integrated downstream of the BWP, removes dissolved solids through a combination of concentration‐driven forward osmosis and pressure driven reverse osmosis. The integrated system testing planned for this year is expected to produce water that requires only a polishing step to meet potable water requirements for spaceflight. The pilot study in California is being conducted on Golden State Water Company's Yukon wells that have hydrogen sulfide odor, color, total organic carbon, bromide, iron and manganese in addition to ammonia. A treatment evaluation, conducted in 2011, recommended the testing of biological oxidation filtration for the removal of ammonia and production of biologically stable water. An 8‐month pilot testing program was conducted to develop and optimize key design and operational variables. Steadystate operational data was collected to demonstrate long‐term performance and inform California Department of Public Health permitting of the full‐scale process. As ammonia continues to present challenges to water and wastewater systems, innovative strategies such as biological treatment can be applied to successfully manage it. This presentation will discuss application of cutting‐age research being conducted by NASA that will bridge existing information gaps, and benefit municipal utilities.

Pickering, Karen↗

Metrology for femtosecond pulsed x-ray heating in diamond anvil cell experiments at the European XFEL: Revisiting the iron phase diagram up to 150 GPa

The development of pulsed intense x-ray sources, such as free electron laser, offers new avenues for high pressure experiments. Here, we study the feasibility and metrology of x-ray heating in diamond anvil cells at the European x-ray free electron laser. This method enables one to volumetrically heat the sample while inhibiting chemical migration and probing the crystallographic structure of the sample throughout the heating with a high repetition rate. We focus our study on iron, whose phase diagram is well established up to 100 GPa, to explore the possibilities and limitations of this technique. We volumetrically heat iron samples at starting pressures ranging from 10 to 138 GPa, using the x-ray beam pulsed at 4.5 MHz in a serial pump-and-probe experimental design. Experimental challenges arise from temperature gradients within the sample, changes in temperature at the 100 ns timescale, the difficulty of direct temperature estimates, the effect of thermal pressure, and the presence of metastable crystallites due to rapid cycles of heating and cooling. Hence, we develop a multi-crystal-like data processing method that allows us to account for sample heterogeneity in probed conditions. We then calibrate our measurements using known physical properties of iron under pressure. Thermal pressure in our experiments increases from 4% of the isochoric prediction at 10 GPa to 23% at 138 GPa, and we show that our data are in agreement with most previous observations of iron in this pressure range. The method can now be implemented at higher pressures and temperatures and on materials with unknown phase diagrams.

Materials science↗

Conflict-free trajectory planning for air traffic control automation

As the traffic demand continues to grow within the National Airspace System (NAS), the need for long-range planning (30 minutes plus) of arrival traffic increases greatly. Research into air traffic control (ATC) automation at ARC has led to the development of the Center-TRACON Automation System (CTAS). CTAS determines optimum landing schedules for arrival traffic and assists controllers in meeting those schedules safely and efficiently. One crucial element in the development of CTAS is the capability to perform long-range (20 minutes) and short-range (5 minutes) conflict prediction and resolution once landing schedules are determined. The determination of conflict-free trajectories within the Center airspace is particularly difficult because of large variations in speed and altitude. The paper describes the current design and implementation of the conflict prediction and resolution tools used to generate CTAS advisories in Center airspace. Conflict criteria (separation requirements) are defined and the process of separation prediction is described. The major portion of the paper will describe the current implementation of CTAS conflict resolution algorithms in terms of the degrees of freedom for resolutions as well as resolution search techniques. The tools described in this paper have been implemented in a research system designed to rapidly develop and evaluate prototype concepts and will form the basis for an operational ATC automation system.

Slattery, Rhonda↗

Image Processing In Laser-Beam-Steering Subsystem

Conceptual design of image-processing circuitry developed for proposed tracking apparatus described in "Beam-Steering Subsystem For Laser Communication" (NPO-19069). In proposed system, desired frame rate achieved by "windowed" readout scheme in which only pixels containing and surrounding two spots read out and others skipped without being read. Image data processed rapidly and efficiently to achieve high frequency response.

Lesh, James R.↗

Making sense from space-time data in laboratory experiments on space plasma processes

A number of visualization techniques are discussed in a laboratory experiment designed to study phenomena that occur in space. Visualization tools are used to design the apparatus, collect data, and make one-, two-, and three-dimensional plots of the results. These tools are an indispensable part of the experiment because the data sets are hundreds of megabytes in size and rapid turnaround is required.

Gekelman, Walter↗

Versatile Turbine Disk Alloy Designed and Processed for Higher Temperature Applications

Advanced turbine engine configurations using higher temperature combustor and airfoil concepts require compressor and turbine disks that can withstand temperatures higher than the 650 C typical of current engines. This requires disk alloy and processing improvements. A versatile disk alloy was needed that could be given either fine grain heat treatments for high strength and fatigue and creep resistance up to 704 C or given coarse grain heat treatments for high strength and creep and dwell crack-growth resistance at higher temperatures. This alloy could produce disks with uniform microstructures and properties, as well as with varied, optimized microstructures at disk bore and rim sections. A series of experimental disk alloys were designed and processed to give subscale disks about 13 cm in diameter and 4 cm thick. These alloys had varying levels of key elements to affect mechanical properties and change the "solvus" solution heat-treatment temperature necessary to produce coarse grain microstructures. Disks were given coarse grain heat treatments followed by rapid oil quenching and slower fan air quenching. These heat treatments were intended to simulate the cooling paths of rapidly cooled full-scale disks at the outermost rim and interior bore locations, respectively. Preliminary quench tests of tensile specimens and coin-size minidisks had indicated that alloys having high solvus temperatures were more prone to cracking during rapid quenching from coarse grain heat treatments. These findings were confirmed in the subscale disks, where such alloys did form undesirable quench cracks. Mechanical tests were performed on specimens from subscale disks given these coarse grain heat treatments, as well as on specimens given a fine grain heat treatment. Tensile, creep, and crack growth tests were performed at 704 C and higher temperatures. A versatile alloy was identified that had a low solvus temperature for resistance to quench cracking as well as an optimal combination of high levels of strengthening refractory elements that produced balanced high mechanical properties for both fine grain and coarse grain microstructures. This low-solvus, high-refractory (LSHR) alloy has been scaled-up to produce prototype full-scale turbine disks typical of regional jet turbofan engines. Disks were successfully heat treated to give uniform coarse grain and uniform fine grain microstructures. Additional disks were given a NASA dual microstructure heat treatment (DMHT) that intentionally varied the solution heat-treatment temperatures between the disk rim and bore (re f. 1). The disk rim was heated to a high enough temperature to produce a coarse grain microstructure, while the bore was maintained at a lower temperature to produce a fine grain microstructure (see the figure). This DMHT can produce optimal high strength, fatigue, and creep resistance up to 704 C in the cooler running disk bore, and high strength, creep resistance, and dwell crack growth resistance at higher temperatures for the hotter disk rim. Extensive mechanical testing is being initiated to compare the mechanical properties of the uniform and DMHT disks.

Gabb, TImothy P.↗

Automated Production of Movies on a Cluster of Computers

A method of accelerating and facilitating production of video and film motion-picture products, and software and generic designs of computer hardware to implement the method, are undergoing development. The method provides for automation of most of the tedious and repetitive tasks involved in editing and otherwise processing raw digitized imagery into final motion-picture products. The method was conceived to satisfy requirements, in industrial and scientific testing, for rapid processing of multiple streams of simultaneously captured raw video imagery into documentation in the form of edited video imagery and video derived data products for technical review and analysis. In the production of such video technical documentation, unlike in production of motion-picture products for entertainment, (1) it is often necessary to produce multiple video derived data products, (2) there are usually no second chances to repeat acquisition of raw imagery, (3) it is often desired to produce final products within minutes rather than hours, days, or months, and (4) consistency and quality, rather than aesthetics, are the primary criteria for judging the products. In the present method, the workflow has both serial and parallel aspects: processing can begin before all the raw imagery has been acquired, each video stream can be subjected to different stages of processing simultaneously on different computers that may be grouped into one or more cluster(s), and the final product may consist of multiple video streams. Results of processing on different computers are shared, so that workers can collaborate effectively.

Nail, Jasper↗

Spinoff 2012

Topics covered include: Water Treatment Technologies Inspire Healthy Beverages; Dietary Formulas Fortify Antioxidant Supplements; Rovers Pave the Way for Hospital Robots; Dry Electrodes Facilitate Remote Health Monitoring; Telescope Innovations Improve Speed, Accuracy of Eye Surgery; Superconductors Enable Lower Cost MRI Systems; Anti-Icing Formulas Prevent Train Delays; Shuttle Repair Tools Automate Vehicle Maintenance; Pressure-Sensitive Paints Advance Rotorcraft Design Testing; Speech Recognition Interfaces Improve Flight Safety; Polymers Advance Heat Management Materials for Vehicles; Wireless Sensors Pinpoint Rotorcraft Troubles; Ultrasonic Detectors Safely Identify Dangerous, Costly Leaks; Detectors Ensure Function, Safety of Aircraft Wiring; Emergency Systems Save Tens of Thousands of Lives; Oxygen Assessments Ensure Safer Medical Devices; Collaborative Platforms Aid Emergency Decision Making; Space-Inspired Trailers Encourage Exploration on Earth; Ultra-Thin Coatings Beautify Art; Spacesuit Materials Add Comfort to Undergarments; Gigapixel Images Connect Sports Teams with Fans; Satellite Maps Deliver More Realistic Gaming; Elemental Scanning Devices Authenticate Works of Art; Microradiometers Reveal Ocean Health, Climate Change; Sensors Enable Plants to Text Message Farmers; Efficient Cells Cut the Cost of Solar Power; Shuttle Topography Data Inform Solar Power Analysis; Photocatalytic Solutions Create Self-Cleaning Surfaces; Concentrators Enhance Solar Power Systems; Innovative Coatings Potentially Lower Facility Maintenance Costs; Simulation Packages Expand Aircraft Design Options; Web Solutions Inspire Cloud Computing Software; Behavior Prediction Tools Strengthen Nanoelectronics; Power Converters Secure Electronics in Harsh Environments; Diagnostics Tools Identify Faults Prior to Failure; Archiving Innovations Preserve Essential Historical Records; Meter Designs Reduce Operation Costs for Industry; Commercial Platforms Allow Affordable Space Research; Fiber Optics Deliver Real-Time Structural Monitoring; Camera Systems Rapidly Scan Large Structures; Terahertz Lasers Reveal Information for 3D Images; Thin Films Protect Electronics from Heat and Radiation; Interferometers Sharpen Measurements for Better Telescopes; and Vision Systems Illuminate Industrial Processes.

Source record↗

Surface-Height Determination of Crevassed Glaciers-Mathematical Principles of an Autoadaptive Density-Dimension Algorithm and Validation Using ICESat-2 Simulator (SIMPL) Data

Glacial acceleration is a main source of uncertainty in sea-level-change assessment. Measurement of ice-surface heights with a spatial and temporal resolution that not only allows elevation-change calculation, but also captures ice-surface morphology and its changes is required to aid in investigations of the geophysical processes associated with glacial acceleration.The Advanced Topographic Laser Altimeter System aboard NASAs future ICESat-2 Mission (launch 2017) will implement multibeam micropulse photon-counting lidar altimetry aimed at measuring ice-surface heights at 0.7-m along-track spacing. The instrument is designed to resolve spatial and temporal variability of rapidly changing glaciers and ice sheets and the Arctic sea ice. The new technology requires the development of a new mathematical algorithm for the retrieval of height information.We introduce the density-dimension algorithm (DDA) that utilizes the radial basis function to calculate a weighted density as a form of data aggregation in the photon cloud and considers density an additional dimension as an aid in auto-adaptive threshold determination. The auto-adaptive capability of the algorithm is necessary to separate returns from noise and signal photons under changing environmental conditions. The algorithm is evaluated using data collected with an ICESat-2 simulator instrument, the Slope Imaging Multi-polarization Photon-counting Lidar, over the heavily crevassed Giesecke Braer in Northwestern Greenland in summer 2015. Results demonstrate that ICESat-2 may be expected to provide ice-surface height measurements over crevassed glaciers and other complex ice surfaces. The DDA is generally applicable for the analysis of airborne and spaceborne micropulse photon-counting lidar data over complex and simple surfaces.

Herzfeld, Ute C.↗

Waterhammer Transient Simulation and Model Anchoring for the Robotic Lunar Lander Propulsion System

Waterhammer transients have the potential to adversely impact propulsion system design if not properly addressed. Waterhammer can potentially lead to system plumbing, and component damage. Multi-thruster propulsion systems also develop constructive/destructive wave interference which becomes difficult to predict without detailed models. Therefore, it is important to sufficiently characterize propulsion system waterhammer in order to develop a robust design with minimal impact to other systems. A risk reduction activity was performed at Marshall Space Flight Center to develop a tool for estimating waterhammer through the use of anchored simulation for the Robotic Lunar Lander (RLL) propulsion system design. Testing was performed to simulate waterhammer surges due to rapid valve closure and consisted of twenty-two series of waterhammer tests, resulting in more than 300 valve actuations. These tests were performed using different valve actuation schemes and three system pressures. Data from the valve characterization tests were used to anchor the models that employed MSCSoftware.EASY5 v.2010 to model transient fluid phenomena by using transient forms of mass and energy conservation. The anchoring process was performed by comparing initial model results to experimental data and then iterating the model input to match the simulation results with the experimental data. The models provide good correlation with experimental results, supporting the use of EASY5 as a tool to model fluid transients and provide a baseline for future RLL system modeling. This paper addresses tasks performed during the waterhammer risk reduction activity for the RLL propulsion system. The problem of waterhammer simulation anchoring as applied to the RLL system is discussed with results from the corresponding experimental valve tests. Important factors for waterhammer mitigation are discussed along with potential design impacts to the RLL propulsion system.

Stein, William B.↗

Application of jet-shear-layer mixing and effervescent atomization to the development of a low-NO(x) combustor

An investigation was conducted to develop appropriate technologies for a low-NO(x), liquid-fueled combustor. The combustor incorporates an effervescent atomizer used to inject fuel into a premixing duct. Only a fraction of the combustion air is used in the premixing process to avoid autoignition and flashback problems. This fuel-rich mixture is introduced into the remaining combustion air by a rapid jet-shear-layer-mixing process involving radial fuel-air jets impinging on axial air jets in the primary combustion zone. Computational analysis was used to provide a better understanding of the fluid dynamics that occur in jet-shear-layer mixing and to facilitate a parametric analysis appropriate to the design of an optimum low-NO(x) combustor. A number of combustor configurations were studied to assess the key combustor technologies and to validate the modeling code. The results from the experimental testing and computational analysis indicate a low-NO(x) potential for the jet-shear-layer combustor. Key parameters found to affect NO(x) emissions are the primary combustion zone fuel-air ratio, the number of axial and radial jets, the aspect ratio and radial location of the axial air jets, and the radial jet inlet hole diameter. Each of these key parameters exhibits a low-NO(x) point from which an optimized combustor was developed. Using the parametric analysis, NO(x) emissions were reduced by a factor of 3 as compared with the emissions from conventional, liquid-fueled combustors operating at cruise conditions. Further development promises even lower NO(x) with high combustion efficiency.

Colantonio, Renato Olaf↗