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At least 37 records · Page 2

Software Development for SonicSonde Instrumentation Suite

The SonicSonde is an innovative weather instrumentation suite for boundary layer sampling. Software development included creating a graphical user interface (GUI) to receive, process, archive, and display data in real-time. Targeted at the Windows operating system but with multi-platform extensibility in mind, the GUI was developed using Qt 5.14 in C++. A key design consideration was to allow for tailored displays and analysis while also permitting additional sensors to be added to the platform. As such, the application relies heavily on flexible interfaces and multithreading processing for capturing, modelling, and plotting data. The object-oriented nature of Qt made it ideal for this purpose. The application supports input through live serial streams and static .csv or .dat files, custom meteorological graphs, and user-dictated panel views and output intervals. Additionally, the GUI displays real-time information about the state of the instrument. The versatility of the SonicSonde will allow meteorologists and researchers to perform or better support a variety of aeronautic and atmospheric missions.

meterology↗

LSAFE: a Lightweight Static Analysis Framework for binary Executables

Static analysis is a widely used technique for analyzing various aspects of programs. However, as programs become more complex, static analysis tools require larger resources, such as CPU time and memory, to perform the same tasks. Moreover, the source code of programs may not always be accessible, requiring static analysis to be performed on the binary executable code directly. To overcome these challenges, we propose a lightweight static analysis framework called LSAFE, which constructs control flow graphs (CFGs) and data dependency graphs (DDGs) of target programs with optimized performance in terms of CPU and memory usage. We evaluated the proposed framework using both Spec benchmark programs and real-world industrial applications, and found that it outperformed Angr, an existing state-of-the-art static analysis tool. Additionally, we demonstrate a case study that utilizes the CFG generated by LSAFE to detect memory leaks.

Qu, Guangzhi↗

Curved flow wind tunnnel test of F-18 aircraft

The curved flow capability of a stability wind tunnel was used to investigate the lateral directional characteristics of an F-18 aircraft. The model is described and the procedures used to obtain and correct the data and a graphical presentation of the results are presented. The results include graphs of lateral directional derivatives versus sideslip or static plots, the lateral directional static stability derivatives versus angle of attack, and finally the lateral directional derivatives versus nondimensional yaw rate for different angles of attack and sideslip. Results are presented for several configurations including complete, complete without vertical tails, complete without horizontal tails, fuselage wing and fuselage alone. Each of these were tested with and without wing leading edge extensions.

Lutze, F. H.↗

From computer images to video presentation: Enhancing technology transfer

With NASA placing increased emphasis on transferring technology to outside industry, NASA researchers need to evaluate many aspects of their efforts in this regard. Often it may seem like too much self-promotion to many researchers. However, industry's use of video presentations in sales, advertising, public relations and training should be considered. Today, the most typical presentation at NASA is through the use of vu-graphs (overhead transparencies) which can be effective for text or static presentations. For full blown color and sound presentations, however, the best method is videotape. In fact, it is frequently more convenient due to its portability and the availability of viewing equipment. This talk describes techniques for creating a video presentation through the use of a combined researcher and video professional team.

Beam, Sherilee F.↗

An Automated Method for Identifying Inconsistencies within Diagrammatic Software Requirements Specifications

The development of large-scale, composite software in a geographically distributed environment is an evolutionary process. Often, in such evolving systems, striving for consistency is complicated by many factors, because development participants have various locations, skills, responsibilities, roles, opinions, languages, terminology and different degrees of abstraction they employ. This naturally leads to many partial specifications or viewpoints. These multiple views on the system being developed usually overlap. From another aspect, these multiple views give rise to the potential for inconsistency. Existing CASE tools do not efficiently manage inconsistencies in distributed development environment for a large-scale project. Based on the ViewPoints framework the WHERE (Web-Based Hypertext Environment for requirements Evolution) toolkit aims to tackle inconsistency management issues within geographically distributed software development projects. Consequently, WHERE project helps make more robust software and support software assurance process. The long term goal of WHERE tools aims to the inconsistency analysis and management in requirements specifications. A framework based on Graph Grammar theory and TCMJAVA toolkit is proposed to detect inconsistencies among viewpoints. This systematic approach uses three basic operations (UNION, DIFFERENCE, INTERSECTION) to study the static behaviors of graphic and tabular notations. From these operations, subgraphs Query, Selection, Merge, Replacement operations can be derived. This approach uses graph PRODUCTIONS (rewriting rules) to study the dynamic transformations of graphs. We discuss the feasibility of implementation these operations. Also, We present the process of porting original TCM (Toolkit for Conceptual Modeling) project from C++ to Java programming language in this thesis. A scenario based on NASA International Space Station Specification is discussed to show the applicability of our approach. Finally, conclusion and future work about inconsistency management issues in WHERE project will be summarized.

Zhang, Zhong↗

Harnessing distributed GPU computing for generalizable graph convolutional networks in power grid reliability assessments

Although machine learning (ML) has emerged as a powerful tool for rapidly assessing grid contingencies, prior studies have largely considered a static grid topology in their analyses. This limits their application, since they need to be re-trained for every new topology. Here, this paper explores the development of generalizable graph convolutional network (GCN) models by pre-training them across a range of grid topologies and contingency types. We found that a GCN model with auto-regressive moving average (ARMA) layers with a line graph representation of the grid offered the best predictive performance in predicting voltage magnitudes (VM) and voltage angles (VA). We introduced the concept of phantom nodes to consider disparate grid topologies with a varying number of nodes and lines. For pre-training the GCN ARMA model across a variety of topologies, distributed graphics processing unit (GPU) computing afforded us significant training scalability. The predictive performance of this model on grid topologies that were part of the training data is substantially better than the direct current (DC) approximation. Although direct application of the pre-trained model to topologies that are not part of the grid is not particularly satisfactory, fine-tuning with small amounts of data from a specific topology of interest significantly improves predictive performance. In general, this paper highlights the feasibility of training large-scale GNN models to assess the reliability of power grids by considering a wide variety of grid topologies and contingency types. With the advent of foundational models in ML and the exponential increase in GPU computing clusters, generalizable ML models will significantly enhance how utilities manage power systems and make decisions in real-time or near-real-time.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Algorithms for Automatic Alignment of Arrays

Aggregate data objects (such as arrays) are distributed across the processor memories when compiling a data-parallel language for a distributed-memory machine. The mapping determines the amount of communication needed to bring operands of parallel operations into alignment with each other. A common approach is to break the mapping into two stages: an alignment that maps all the objects to an abstract template, followed by a distribution that maps the template to the processors. This paper describes algorithms for solving the various facets of the alignment problem: axis and stride alignment, static and mobile offset alignment, and replication labeling. We show that optimal axis and stride alignment is NP-complete for general program graphs, and give a heuristic method that can explore the space of possible solutions in a number of ways. We show that some of these strategies can give better solutions than a simple greedy approach proposed earlier. We also show how local graph contractions can reduce the size of the problem significantly without changing the best solution. This allows more complex and effective heuristics to be used. We show how to model the static offset alignment problem using linear programming, and we show that loop-dependent mobile offset alignment is sometimes necessary for optimum performance. We describe an algorithm with for determining mobile alignments for objects within do loops. We also identify situations in which replicated alignment is either required by the program itself or can be used to improve performance. We describe an algorithm based on network flow that replicates objects so as to minimize the total amount of broadcast communication in replication.

Chatterjee, Siddhartha↗

Fast GPU-Based Generation of Large Graph Networks From Degree Distributions

Synthetically generated, large graph networks serve as useful proxies to real-world networks for many graph-based applications. The ability to generate such networks helps overcome several limitations of real-world networks regarding their number, availability, and access. Here, we present the design, implementation, and performance study of a novel network generator that can produce very large graph networks conforming to any desired degree distribution. The generator is designed and implemented for efficient execution on modern graphics processing units (GPUs). Given an array of desired vertex degrees and number of vertices for each desired degree, our algorithm generates the edges of a random graph that satisfies the input degree distribution. Multiple runtime variants are implemented and tested: 1) a uniform static work assignment using a fixed thread launch scheme, 2) a load-balanced static work assignment also with fixed thread launch but with cost-aware task-to-thread mapping, and 3) a dynamic scheme with multiple GPU kernels asynchronously launched from the CPU. The generation is tested on a range of popular networks such as Twitter and Facebook, representing different scales and skews in degree distributions. Results show that, using our algorithm on a single modern GPU (NVIDIA Volta V100), it is possible to generate large-scale graph networks at rates exceeding 50 billion edges per second for a 69 billion-edge network. GPU profiling confirms high utilization and low branching divergence of our implementation from small to large network sizes. For networks with scattered distributions, we provide a coarsening method that further increases the GPU-based generation speed by up to a factor of 4 on tested input networks with over 45 billion edges.

97 MATHEMATICS AND COMPUTING↗

Intelligent Experiments through Real-Time AI: Fast Data Processing and Autonomous Detector Control for High-Energy Nuclear Experiments

The aim of this project is to develop software and hardware for fast real-time data processing and autonomous detector control and calibration for the sPHENIX and the future EIC experiments. Below summarizes Georgia Tech team efforts in the past year: 1. We developed a real-time clustering algorithm and FPGA-based pipeline architecture for processing fired pixel data from ALPIDE sensors in sPHENIX experiments. Our Columnar Clustering Co-Design introduces a hardware-aware, stream-friendly approach that segments pixel data by column pairs using a Column Pair Clustering (CPC) strategy, followed by Cluster Stitching to merge adjacent subclusters. Implemented in Vitis HLS, the pipeline comprises five stages—read-in, subclustering, stitching, analysis, and write-out—connected by tagged HLS streams with custom end-of-event signaling for robust synchronization. We designed a pipelined dataflow model optimized for throughput, low latency, and minimal buffering, enabling scalable clustering across events of arbitrary size. Our system maintains spatial precision via center-of-mass and shape key extraction and efficiently handles edge cases such as fragmented or nested clusters. Compared against DBSCAN in both software and hardware, our approach demonstrates competitive performance under FPGA constraints. 2. We also conducted a comprehensive algorithm-to-hardware co-design of connected component analysis tailored for sPHENIX experiments, focusing on real-time, low-latency processing using FPGAs and High-Level Synthesis (HLS). Starting from a Python-based particle tracking pipeline, the team translated the core logic—graph traversal via DFS and Union-Find—into an HLS-compatible C++ model, replacing dynamic memory and recursion with static arrays and pipelined control flow. The final design includes a fully streamed and dataflow-compatible Union-Find kernel optimized across five iterations, incorporating loop pipelining, array partitioning, AXI/FIFO interface tuning, and function flattening. Experimental results show up to 14.8× speedup over the CPU baseline, reducing per-graph latency to 1.58 μs and demonstrating strong resource efficiency with only ~7k LUTs and zero BRAM usage. The design maintains functional correctness against the Python reference using a Python-based C-simulation framework and Mean Squared Error metrics. This work validates the potential of HLS-driven FPGA designs for edge-level HEP data acquisition, laying a scalable foundation for future integration with real-time detector pipelines and multi-graph processing systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Axial Fatigue Tests at Zero Mean Stress of 24S-T Aluminum-alloy Sheet with and Without a Circular Hole

Axial fatigue tests were made on 189 coupon specimens of 0.032-inch 24S-T aluminum-alloy sheet and a few supplementary specimens of 0.004-inch sheet. The mean load was zero. The specimens were restrained against lateral buckling by lubricated solid guides described in a previous report on this project. About two-thirds of the 0.032-inch specimens were plain coupons nominally free from stress raisers. The remainder contained a 0.1285-inch drilled hole at the center where the reduced section was 0.5 inch wide. S-N diagrams were obtained for cycles to failure between about 1000 and 10 to the 7th power cycles for the plain specimens and 17 and 10 to the 7th power cycles for the drilled specimens. The fatigue stress concentration factor increased from about 1.08 for a stress amplitude causing failure at 0.25 cycles (static) to a maximum of 1.83 at 15,000 cycles and then decreased gradually. The graph for the drilled specimens showed less scatter than that for the plain specimens.

TESTING MACHINES, FATIGUE↗

Automatic inspection of program state in an uncooperative environment

Abstract The program state is formed by the values that the program manipulates. These values are stored in the stack, in the heap, or in static memory. The ability to inspect the program state is useful as a debugging or as a verification aid. Yet, there exists no general technique to insert inspection points in type‐unsafe languages such as C or C++. The difficulty comes from the need to traverse the memory graph in a so‐called uncooperative environment. In this article, we propose an automatic technique to deal with this problem. We introduce a static code transformation approach that inserts in a program the instrumentation necessary to report its internal state. Our technique has been implemented in LLVM. It is possible to adjust the granularity of inspection points trading precision for performance. In this article, we demonstrate how to use inspection points to debug compiler optimizations; to augment benchmarks with verification code; and to visualize data structures.

Magalhães, José Wesley de Souza↗

SENTRA: A Modular Computational Graph Framework for Critical Mineral and Materials Supply Chains: Part I: Network Construction Latent-Quantity Estimation, and Temporal Graph Forecasting

Global supply chains for critical minerals and materials are complex, evolving networks of countries, products, production stages, and trade relationships. Existing analytical approaches are limited by fragmented data and static network representations that do not capture the dynamic production dependencies linking raw materials, intermediate products, and final goods across multiple countries. Trade and production statistics provide only a partial view of domestic production, inventories, and material flows, making it difficult to identify indirect sourcing pathways, hidden dependencies, and embedded foreign exposures. This paper introduces the Supply Chain Exposure Network Tracking and Risk Assessment (SENTRA) framework, a modular graph-based computational framework for constructing, analyzing, and forecasting dynamic supply chain networks. As the first paper in a three-part methodological series, it establishes the computational foundation of SENTRA by constructing a temporal attributed multi-relational graph whose nodes represent product–country pairs and whose edges encode observed trade and within-country value-chain relationships. Statistical estimation and constrained optimization recover latent production, final demand, and product input dependency coefficients while enforcing economic accounting constraints. Graph-derived exposure measures quantify direct, transshipment, value-chain, and multi-hop supply chain dependencies independently of the forecasting model. A temporal graph forecasting architecture based on a relational graph neural network then forecasts the evolution of the graph under mass-balance constraints with distribution-free conformal uncertainty quantification. Validation on the global aluminum supply chain shows that the learned graph representations recover economically meaningful supply chain structure, accurately forecast out-of-sample trade relationships, and produce well-calibrated prediction intervals. Subsequent papers apply this computational foundation to exposure assessment, disruption analysis, and scenario-based policy analysis, and extend the framework to multimaterial supply chain modeling and decision support.

36 MATERIALS SCIENCE↗

PDA: A coupling of knowledge and memory for case-based reasoning

Problem solving in most domains requires reference to past knowledge and experience whether such knowledge is represented as rules, decision trees, networks or any variant of attributed graphs. Regardless of the representational form employed, designers of expert systems rarely make a distinction between the static and dynamic aspects of the system's knowledge base. The current paper clearly distinguishes between knowledge-based and memory-based reasoning where the former in its most pure sense is characterized by a static knowledge based resulting in a relatively brittle expert system while the latter is dynamic and analogous to the functions of human memory which learns from experience. The paper discusses the design of an advisory system which combines a knowledge base consisting of domain vocabulary and default dependencies between concepts with a dynamic conceptual memory which stores experimental knowledge in the form of cases. The case memory organizes past experience in the form of MOPs (memory organization packets) and sub-MOPs. Each MOP consists of a context frame and a set of indices. The context frame contains information about the features (norms) common to all the events and sub-MOPs indexed under it.

Bharwani, S.↗

ATAMM enhancement and multiprocessing performance evaluation

The algorithm to architecture mapping model (ATAAM) is a Petri net based model which provides a strategy for periodic execution of a class of real-time algorithms on multicomputer dataflow architecture. The execution of large-grained, decision-free algorithms on homogeneous processing elements is studied. The ATAAM provides an analytical basis for calculating performance bounds on throughput characteristics. Extension of the ATAMM as a strategy for cyclo-static scheduling provides for a truly distributed ATAMM multicomputer operating system. An ATAAM testbed consisting of a centralized graph manager and three processors is described using embedded firmware on 68HC11 microcontrollers.

Stoughton, John W.↗

Thermal environment effects on strength and impact properties of boron-aluminum composites

A systematic study was conducted regarding the degradation of fracture strength and impact energy in commercial B-Al composites in both static and cyclic thermal environments. The composites used in the study contained approximately 50 vol % boron fibers, unidirectionally aligned in either a 6061 Al or 1100 Al matrix. The tensile strengths of the composites after 3000 thermal cycles as a function of upper cycle temperature are presented in graphs. The temperature at which the strengths of 6061 Al matrix, B-Al composites were significantly degraded after 3000 cycles was noticeably higher than that for the 1100 Al matrix composites. Static heating at 420 C resulted in no significant strength degradation for the 6061 Al matrix composites. In the case of 1100 matrix composites, some degradation was observed at 420 C but markedly less than in the composites cycled to 420 C.

Grimes, H. H.↗

Real-Time Inhibitor Recession Measurements in Two Space Shuttle Reusable Solid Rocket Motors

Real-time internal motor insulation char line recession measurements have been evaluated for two full-scale static tests of the Space Shuttle Reusable Solid Rocket Motor (RSRM). These char line recession measurements were recorded on the forward facing propellant grain inhibitors to better understand the thermal performance of these inhibitors. The RSRM propellant grain inhibitors are designed to erode away during motor operation, thus making it difficult to use post-fire observations to determine inhibitor thermal performance. Therefore, this new internal motor instrumentation is invaluable in establishing an accurate understanding of inhibitor recession versus motor operation time. The data for the first test was presented at the 37th AIAA/ASME/SAE/ASEE Joint Propulsion Conference and Exhibit (AIAA 2001-3280) in July 2001. Since that time, a second full scale static test has delivered additional real-time data on inhibitor thermal performance. The evaluation of this data is presented in this paper. The second static test, in contrast to the first test, used a slightly different arrangement of instrumentation in the inhibitors. This instrumentation has yielded a better understanding of the inhibitor time dependent inboard tip recession. Graphs of inhibitor recession profiles with time are presented. Inhibitor thermal ablation models have been created from theoretical principals. The model predictions compare favorably with data from both tests. This verified modeling effort is important to support new inhibitor designs for a five segment Space Shuttle solid rocket motor. The internal instrumentation project on RSRM static tests is providing unique opportunities for other real-time internal motor measurements that could not otherwise be directly quantified.

McWhorter, B. B.↗

Reanalysis procedure for large structural systems

Global-basis-vector approximate reanalysis techniques for use in automated structural optimization schemes are developed and demonstrated. The vibrational response of a modified structure (MS) is estimated by lumping the design variables into a single tracing parameter, applying an operator splitting procedure to express the FEM equations of the MS in terms of the original-structure equations plus correction terms, and reducing the MS equations via a classical Bubnov-Galerkin scheme. The sensitivity of the vibrational response to structural modifications is evaluated, and the relationship between this method and the preconditioned conjugate-gradient method (Noor and Peters, 1988) is explored. Numerical results for linear static and free vibration problems involving beamlike lattices, double-layered hexahedral grids, and structural gridworks are presented in tables and graphs and briefly characterized.

Noor, Ahmed K.↗

Matching Curved Lattices to Anisotropic Tangent Planes

Radial quantization would be the ideal formalism for studying strongly-coupled near-conformal quantum field theories but it requires the ability to perform lattice calculations on static, curved manifolds, specifically a very long cylinder whose cross section is a sphere. Smoothly discretizing the surface of a sphere requires a graph with unequal edge lengths. The geometry of such graphs is well understood since 1961 using Regge Calculus. But, lattice quantum field theories are defined in terms of couplings which appear in the action rather than edge lengths and so the relationship between couplings and lengths must be determined dynamically. A simple example is computing the ratio of spatial to temporal lattice spacings in anisotropic lattice QCD. I will discuss our conjecture that computing anisotropic lattice spacing ratios on affine transformations of regular flat lattices is sufficient to determine coupling assignments on curved lattices.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗