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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 325 records · Page 18

Rapid measurement of soluble xylo-oligomers using near-infrared spectroscopy (NIRS) and multivariate statistics: calibration model development and practical approaches to model optimization

Rapid monitoring of biomass conversion processes using techniques such as near-infrared (NIR) spectroscopy can be substantially quicker and less labor-, resource-, and energy-intensive than conventional measurement techniques such as gas or liquid chromatography (GC or LC) due to the lack of solvents and preparation methods, as well as removing the need to transfer samples to an external lab for analytical evaluation. The purpose of this study was to determine the feasibility of rapid monitoring of a biomass conversion process using NIR spectroscopy combined with multivariate statistical modeling, and to examine the impact of (1) subsetting the samples in the original dataset by process location and (2) reducing the spectral range used in the calibration model on model performance. We develop multivariate calibration models for the concentrations of soluble xylo-oligosaccharides (XOS), monomeric xylose, and total solids at multiple points in a biomass conversion process which produces and then purifies XOS compounds from sugar cane bagasse. A single model using samples from multiple locations in the process stream showed acceptable performance as measured by standard statistical measures. However, compared to the single model, we show that separate models built by segregating the calibration samples according to process location show improved performance. We also show that combining an understanding of the sample spectra with simple multivariate analysis tools can result in a calibration model with a substantially smaller spectral range that provides essentially equal performance to the full-range model. We demonstrate that real-time monitoring of soluble xylo-oligosaccharides (XOS), monomeric xylose, and total solids concentration at multiple points in a process stream using NIR spectroscopy coupled with multivariate statistics is feasible. Segregation of sample populations by process location improves model performance. Models using a reduced spectral range containing the most relevant spectral signatures show very similar performance to the full-range model, reinforcing the importance of performing robust exploratory data analysis before beginning multivariate modeling.

09 BIOMASS FUELS↗

An Optimized Multicolor Point-Implicit Solver for Unstructured Grid Applications on Graphics Processing Units

In the field of computational fluid dynamics, the Navier-Stokes equations are often solved using an unstructuredgrid approach to accommodate geometric complexity. Implicit solution methodologies for such spatial discretizations generally require frequent solution of large tightly-coupled systems of block-sparse linear equations. The multicolor point-implicit solver used in the current work typically requires a significant fraction of the overall application run time. In this work, an efficient implementation of the solver for graphics processing units is proposed. Several factors present unique challenges to achieving an efficient implementation in this environment. These include the variable amount of parallelism available in different kernel calls, indirect memory access patterns, low arithmetic intensity, and the requirement to support variable block sizes. In this work, the solver is reformulated to use standard sparse and dense Basic Linear Algebra Subprograms (BLAS) functions. However, numerical experiments show that the performance of the BLAS functions available in existing CUDA libraries is suboptimal for matrices representative of those encountered in actual simulations. Instead, optimized versions of these functions are developed. Depending on block size, the new implementations show performance gains of up to 7x over the existing CUDA library functions.

Zubair, Mohammad↗

Precise Pointing for Radio Science Occultations and Radar Mapping During the Cassini Mission at Saturn

This paper discusses the implementation challenges and lessons learned from radar and radio science pointing observations during the Cassini mission at Saturn. Implementation of the precise desired pointing reveals key issues in the ground system, the flight system, and the pointing paradigm itself. To achieve accurate pointing on some observations, specific workarounds had to be implemented and folded into the sequence development process. Underlying Cassini's pointing system is a remarkable construct known as Inertial Vector Propagation.

Burk, Thomas A.↗

A minimax approach to spatial estimation using affinity matrices

Estimates made in the plane to improve on noisy unbiased estimates were combined. Only a small fraction of points in a giant grid were used to do this, those that are most like a given point. A component of this process defining an affinity matrix of values, indicating which points are relevant to others. Minimax rules are shown to be based on affinity matrices.

Morris, C. N.↗

Image registration system in the Landsat-D production environment

It is the purpose of the considered system to take pieces of imagery, called control point chips (CPC), whose geodetic location has been previously determined and stored, and locate their position in later imagery of the same area. The registration processes are carried out partially on a DEC VAX 780 computer and partially on a Floating Point Systems Array Processor. Typically sets of 20 control points are processed at a time. To process these as sets, and to optimize the use of both machines, operations are grouped into loops instead of a sequential processing for each point. Attention is given to cloud cover assessment, enhancement, correlation techniques, pixel registration, and subpixel registration.

Kiss, P.↗

Parameter estimation for terrain modeling from gradient data

A method is developed for modeling terrain surfaces for use on an unmanned Martian roving vehicle. The modeling procedure employs a two-step process which uses gradient as well as height data in order to improve the accuracy of the model's gradient. Least square approximation is used in order to stochastically determine the parameters which describe the modeled surface. A complete error analysis of the modeling procedure is included which determines the effect of instrumental measurement errors on the model's accuracy. Computer simulation is used as a means of testing the entire modeling process which includes the acquisition of data points, the two-step modeling process and the error analysis. Finally, to illustrate the procedure, a numerical example is included.

Dangelo, K. R.↗

Progressive and instantaneous nature of lithium nucleation discovered by dynamic and operando imaging

The understanding of lithium (Li) nucleation and growth is important to design better electrodes for high-performance batteries. However, the study of Li nucleation process is still limited because of the lack of imaging tools that can provide information of the entire dynamic process. We developed and used an operando reflection interference microscope (RIM) that enables real-time imaging and tracking the Li nucleation dynamics at a single nanoparticle level. This dynamic and operando imaging platform provides us with critical capabilities to continuously monitor and study the Li nucleation process. We find that the formation of initial Li nuclei is not at the exact same time point, and Li nucleation process shows the properties of both progressive and instantaneous nucleation. In addition, the RIM allows us to track the individual Li nucleus’s growth and extract spatially resolved overpotential map. The nonuniform overpotential map indicates that the localized electrochemical environments substantially influence the Li nucleation.

25 ENERGY STORAGE↗

Integrating Resilience Planning in Distribution System Planning

Electric utilities, regulators, and stakeholders face increasing risks of severe storms, freezes, floods, and heat waves damaging grid infrastructure and causing power outages—and increasing risks of utility equipment igniting wildfires. At the same time, customer electricity rates have risen substantially in recent years, due in part to replacing aging infrastructure and improving resilience to natural hazards and physical threats. To address these challenges, utilities are beginning to move beyond traditional, siloed planning processes to balance resilience with other fundamental grid objectives such as affordability, reliability, safety, and serving new loads. This study presents a framework for states and utilities that want to advance integration of resilience and distribution planning processes to improve planning efficiency, better prioritize cost-effective grid expenditures, and balance planning objectives. The framework includes 7 key integration points between these planning processes: -Strategy process -Data -Threat assessments -Solution identification and prioritization -Optimization opportunities -Consideration of other grid needs -Metrics Lawrence Berkeley National Laboratory reviewed utility distribution system plans and interviewed subject matter experts to identify emerging practices for each of the 7 integration points. This report presents these practices, which can be used as a guide toward more holistic planning and cohesive investment strategies. It also includes 3 case studies to provide practical examples of how utilities apply such integrated planning processes: two pole hardening programs and one microgrid planning effort. The report concludes by identifying opportunities for future research.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Electronic device and method for compressing sampled data

An electronic device for compressing sampled data comprises a memory element and a processing element. The memory element is configured to store sampled data points and sampled times. The processing element is in electronic communication with the memory element and is configured to receive a plurality of sampled data points, a slope for each sampled data point in succession, the slope being a value of a change between the sampled data point and its successive sampled data point, and store the sampled data point in the memory element when the slope changes in value from a previous sampled data point.

Morrow, Mitchell Hedges↗

Electronic device and method for compressing sampled data

An electronic device for compressing sampled data comprises a memory element and a processing element. The memory element is configured to store sampled data points and sampled times. The processing element is in electronic communication with the memory element and is configured to receive a plurality of sampled data points, a slope for each sampled data point in succession, the slope being a value of a change between the sampled data point and its successive sampled data point, and store the sampled data point in the memory element when the slope changes in value from a previous sampled data point.

Tohlen, Michael Aaron↗

Electronic device and method for compressing sampled data

An electronic device for compressing sampled data comprises a memory element and a processing element. The memory element is configured to store sampled data points and sampled times. The processing element is in electronic communication with the memory element and is configured to receive a plurality of sampled data points, a slope for each sampled data point in succession, the slope being a value of a change between the sampled data point and its successive sampled data point, and store the sampled data point in the memory element when the slope changes in value from a previous sampled data point.

Morrow, Mitchell Hedges↗

A novel technique for minimizing energy functional using neural networks

An energy functional describes the equilibrium state of a system. In this work, we present a novel technique, Functional Optimization using Neural Networks (FONN), for minimizing the system’s energy. FONN utilizes neural networks to process information at discrete grid points, considering their interactions with neighboring grid points, to update the state of the system. The training process involves formulating a loss function based on the system’s energy, and with the help of multiple fine-tuning steps, the method employs a progressive energy reduction technique that decreases the energy in multiple steps. FONN’s effectiveness is demonstrated across various problems, including the minimization of the heat and Lyapunov energy. Furthermore, the paper explores the minimization of the elastic bending energy with an area constraint.

97 MATHEMATICS AND COMPUTING↗

Geometric verification

Present LANDSAT data formats are reviewed to clarify how the geodetic location and registration capabilities were defined for P-tape products and RBV data. Since there is only one geometric model used in the master data processor, geometric location accuracy of P-tape products depends on the absolute accuracy of the model and registration accuracy is determined by the stability of the model. Due primarily to inaccuracies in data provided by the LANDSAT attitude management system, desired accuracies are obtained only by using ground control points and a correlation process. The verification of system performance with regards to geodetic location requires the capability to determine pixel positions of map points in a P-tape array. Verification of registration performance requires the capability to determine pixel positions of common points (not necessarily map points) in 2 or more P-tape arrays for a given world reference system scene. Techniques for registration verification can be more varied and automated since map data are not required. The verification of LACIE extractions is used as an example.

Grebowsky, G. J.↗

Impactor control of central peak and peak-ring formation

The relation between the depth and diameter of excavation for impacts typically is assumed to be proportional. Such an assumption is consistent with the constant aspect ratio (diameter:depth) observed for simple craters found in a wide range of planetary settings and crater-scaling laws derived from laboratory experiments. Although complex craters exhibit evidence for floor uplift and rim collapse of a transient profile, they are typically thought to resemble initially smaller, simple craters. At large scales, however, early-time processes consume a greater fraction of crater growth and the assumption of late-time equivalence of energy release as a point source becomes inappropriate. The authors propose instead that crater diameter, depth, and impactor penetration represent separable dependent variables that underscore the fundamental difference between impact and point-source explosion excavation processes. An important consequence of this perspective is that central pits, peaks, and rings may represent contrasting target responses to impactor penetration and could provide an important indicator of impactor dimensions.

Schultz, Peter H.↗

Delaunay walk for fast nearest neighbor: accelerating correspondence matching for ICP

Point set registration algorithms such as Iterative Closest Point (ICP) are commonly utilized in time-constrained environments like robotics. Finding the nearest neighbor of a point in a reference 3D point set is a common operation in ICP and frequently consumes at least 90% of the computation time. We introduce a novel approach to performing the distance-based nearest neighbor step based on Delaunay triangulation. This greedy algorithm finds the nearest neighbor of a query point by traversing the edges of the Delaunay triangulation created from a reference 3D point set. Our work integrates the Delaunay traversal into the correspondences search of ICP and exploits the iterative aspect of ICP by caching previous correspondences to expedite each iteration. An algorithmic analysis and comparison is conducted showing an order of magnitude speedup for both serial and vector processor implementation.

3d point cloud processing↗

Simulating Mars: Enabling Testing of the Perseverance Rover Sampling and Caching Subsystem on Earth

The development of the Sampling and Caching Subsystem (SCS) on the JPL Perseverance Rover lies at the intersection of testing, robotics, and geology. The SCS team established three primary system test campaigns and venues to aid in the development of SCS through verification and validation testing – Qualification Model Dirty Testing (QMDT) to provide a venue for testing in a Martian environment, Vehicle System Testbed (VSTB) for testing while integrated with the mobility subsystem on Martian-like terrain, and the Flight Software Testbed (FSWTB) for conducting tests using the flight motor controllers and software system on a hexapod which had the ability to simulate rover tilt. Each venue contributed a vital piece to the SCS building blocks. However, the QMDT venue operating within a 10-ft diameter Thermal Vacuum chamber to simulate Martian environment provided a sui generis opportunity to fine tune the entire sampling and caching process while building the team’s knowledge base about rock drillability, system life, and target selection. On Earth, because Martian rocks are not readily available, the development team must utilize geoanalogs to the rocks and regolith on Mars. Geologists on the team helped establish a set of standard rock types to use for Mars missions, like Basalt, Sandstone, Mudstone, Gypsum, and other related geoanalogs. These geoanalogs are characterized with a standard suite of tests for density, compressibility, and other characteristics to categorize potential drillability. This concept of drillability is what links the geoanalogs on Earth to the samples we collect on Mars. With the simulant characteristics defined, these geoanalog rocks are ready to be drilled into as we do on the Martian surface. A key aspect of interacting with the surface on Mars is rock target identification and selection. The Perseverance robotic system uses the on-board cameras, instrumentation, and software to collect enough information to identify potential scientific targets. With the targets identified, SCS can place the Corer and abrade the surface or collect a sample. For a ground test activity like QMDT, the test team did not have all of the camera and instrumentation systems that the rover does, so the team developed ground test equivalents to process a rock, build a target map, and define the target. The team constructed a Rock Scanning Station to build a 3D point cloud of the rock. This point cloud was then processed and evaluated with predefined and programmed criteria in a Target Downselect Tool. A primary output of the Target Downselect Tool is a defined target that can be uploaded directly to the robotic software system to simulate and build the robotic sequences used in tests. With these insights and programmatic definition of targets, the QMDT test team was able to make the same decisions that the Perseverance surface operations team does. In addition, valuable lessons learned from developing the target selection ground tools and using them were implemented into the tools used for surface operations.

Kim, Junggon↗

Role of geometric dynamic recrystallization in nanocrystalline alloys

Nanocrystalline and near-nano-grained metals are plagued with an overall lack of ductility and formability. This is in part due to their inability to support the dislocation mechanisms or undergo the same types of transformations that conventional coarse-grained metals access in order to increase their workability. Therefore, despite their advanced properties such as high strength, the manufacturing of such fine-grained metals, which exposes them to multi-axial states of stress in operations such as rolling, drawing, extrusion, forging, and bending, has not been possible. In this work, we address this limitation and highlight an important aspect of geometric dynamic recrystallization (GDRX) in nanocrystalline materials as a way to improve manufacturability. In particular, using two different alloy compositions and two different processing techniques, this study points to the fact that if nanocrystalline or near nano metals can be truly stabilized, they can repeatedly undergo the same types of processes that conventional coarse-grained metals endure, increasing both their formability and hence manufacturability. The results reveal that due to a large number of initial high-angle grain boundaries and large applied compressive strains, GDRX is activated in the absence of any discontinuous dynamic recrystallization (DDRX) or continuous dynamic recrystallization (CDRX). This is a unique aspect of stabilized nanocrystalline materials, as traditionally fine-grained metals are not microstructurally stable enough to accommodate such an event.

36 MATERIALS SCIENCE↗

A multiple objective optimization approach to quality control

The use of product quality as the performance criteria for manufacturing system control is explored. The goal in manufacturing, for economic reasons, is to optimize product quality. The problem is that since quality is a rather nebulous product characteristic, there is seldom an analytic function that can be used as a measure. Therefore standard control approaches, such as optimal control, cannot readily be applied. A second problem with optimizing product quality is that it is typically measured along many dimensions: there are many apsects of quality which must be optimized simultaneously. Very often these different aspects are incommensurate and competing. The concept of optimality must now include accepting tradeoffs among the different quality characteristics. These problems are addressed using multiple objective optimization. It is shown that the quality control problem can be defined as a multiple objective optimization problem. A controller structure is defined using this as the basis. Then, an algorithm is presented which can be used by an operator to interactively find the best operating point. Essentially, the algorithm uses process data to provide the operator with two pieces of information: (1) if it is possible to simultaneously improve all quality criteria, then determine what changes to the process input or controller parameters should be made to do this; and (2) if it is not possible to improve all criteria, and the current operating point is not a desirable one, select a criteria in which a tradeoff should be made, and make input changes to improve all other criteria. The process is not operating at an optimal point in any sense if no tradeoff has to be made to move to a new operating point. This algorithm ensures that operating points are optimal in some sense and provides the operator with information about tradeoffs when seeking the best operating point. The multiobjective algorithm was implemented in two different injection molding scenarios: tuning of process controllers to meet specified performance objectives and tuning of process inputs to meet specified quality objectives. Five case studies are presented.

Seaman, Christopher Michael↗