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SSRN 2024年

作者： Tian, Su Du, Haodong Tao, Fei Yu, Wenbin Lim, Joon W. Haehnel, Robert Wenren, Yonghu Allen, Luke Purdue University West LafayetteIN47906 United States U.S. Army Combat Capabilities Development Command Aviation & Missile Center Ames Research Center Moffett FieldCA94035 United States US Army Engineer Research and Development Center Cold Regions Research and Engineering Laboratory HanoverNH03755 United States

Design optimization of composite slender structures such as helicopter rotor blades requires a structural design optimization tool with a fast and accurate evaluation of beam properties. VABS has been widely used by many for decades. However, there lacks a design tool that can make full use of its capabilities. This work proposes a new framework and develops a new toolset named iVABS for this purpose. It is an integration of VABS along with a cross-sectional builder, a versatile parameterization method of composite slender structures, design methods (available via Dakota), and an interface to external analysis tools such as RCAS. Examples are provided to demonstrate the capability of generating proper designs of composite structures that can satisfy the performance requirements. © 2024, The Authors. All rights reserved.

关键词： Structural optimization

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Methodology,progress and challenges of geoscience knowledge graph in International Big Science Program of Deep-Time Digital Earth

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Journal of Geographical Sciences 2025年第5期35卷 1132-1156页

作者： ZHU Yunqiang WANG Qiang WANG Shu SUN Kai WANG Xinbing LV Hairong HU Xiumian ZHANG Jie WANG Bin QIU Qinjun YANG Jie ZHOU Chenghu State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchCASBeijing 100101China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing 210023China University of Chinese Academy of Sciences Beijing 100049China School of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghai 200240China Department of Automation Tsinghua UniversityBeijing 100084China State Key Laboratory for Mineral Deposits Research School of Earth Sciences and EngineeringNanjing UniversityNanjing 210023China State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and TelecommunicationsBeijing 100876China Command Center of Natural Resources Comprehensive Survey China Geological SurveyBeijing 100055China School of Computer Science China University of GeosciencesWuhan 430074China

Deep-time Earth research plays a pivotal role in deciphering the rates,patterns,and mechanisms of Earth's evolutionary processes throughout geological history,providing essential scientific foundations for climate prediction,natural resource exploration,and sustainable planetary *** advance Deep-time Earth research in the era of big data and artificial intelligence,the International Union of Geological Sciences initiated the“Deeptime Digital Earth International Big Science Program”(DDE)in *** the core of this ambitious program lies the development of geoscience knowledge graphs,serving as a transformative knowledge infrastructure that enables the integration,sharing,mining,and analysis of heterogeneous geoscience big *** DDE knowledge graph initiative has made significant strides in three critical dimensions:(1)establishing a unified knowledge structure across geoscience disciplines that ensures consistent representation of geological entities and their interrelationships through standardized ontologies and semantic frameworks;(2)developing a robust and scalable software infrastructure capable of supporting both expert-driven and machine-assisted knowledge engineering for large-scale graph construction and management;(3)implementing a comprehensive three-tiered architecture encompassing basic,discipline-specific,and application-oriented knowledge graphs,spanning approximately 20 geoscience *** its open knowledge framework and international collaborative network,this initiative has fostered multinational research collaborations,establishing a robust foundation for next-generation geoscience research while propelling the discipline toward FAIR(Findable,Accessible,Interoperable,Reusable)data practices in deep-time Earth systems research.

关键词： deep-time Earth geoscience knowledge graph Deep-time Digital Earth International Big Science Program

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Control-Oriented Combustion Modeling for Compression-Ignition Engines Operating With Low Cetane Fuels

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IFAC-PapersOnLine 2023年第3期56卷 631-636页

作者： Omar Ahmed Robert Middleton Anna Stefanopoulou Kenneth Kim Chol-Bum Kweon Department of Mechanical Engineering University of Michigan - Ann Arbor Ann Arbor MI 48109 USA Aberdeen Proving Ground MD 21005 USA U.S. Army Combat Capabilities Development Command Army Research Laboratory

To support the transition toward sustainable alternative fuels in the transportation sector, advanced statistical modeling techniques are needed to characterize and control combustion at low cetane fueling conditions. In this work, a novel control-oriented combustion phasing model is presented that simulates asymmetrical phasing distributions as a function of fuel cetane, fuel injection timing, and electrical power supplied to a thermal ignition assist device. The model was regressed using experimental data from a commercial compression-ignition (CI) engine operating with four fuel blends of cetane number ranging from 25 to 48. The model estimates the mode and median of phasing distributions within 2.4 and 2.6 crank angle degrees (CAD), respectively, over a range of 52 CAD. Additionally, kernel density estimation (KDE) is proposed for nonparametric modeling of torque as a function of phasing. A set of KDE-driven extremum seeking algorithms for learning torque-optimal phasing ranges and probabilistic misfire limits is validated across the multi-fuel data. By using a probabilistic criteria, this approach can permit an acceptable proportion of undesired events to occur before classifying a limit. This feature better suits it for engine operation with low cetane fuels, where late burns and misfires may not be entirely avoidable. This work will facilitate online learning-based control strategies that can enable CI engines to adapt to fuels with a wide range of ignition behaviors.

关键词： Lognormal Statistical Distributions Kernel Density Estimation (KDE) Online Learning Engine Modeling and Control

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CoPeD-Advancing Multi-Robot Collaborative Perception: A Comprehensive Dataset in Real-World Environments

arXiv

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arXiv 2024年

作者： Zhou, Yang Quang, Long Nieto-Granda, Carlos Loianno, Giuseppe The New York University Tandon School of Engineering BrooklynNY11201 United States The U.S. Army Combat Capabilities Development Command Army Research Laboratory AdelphiMD20783 United States

In the past decade, although single-robot perception has made significant advancements, the exploration of multi-robot collaborative perception remains largely unexplored. This involves fusing compressed, intermittent, limited, heterogeneous, and asynchronous environmental information across multiple robots to enhance overall perception, despite challenges like sensor noise, occlusions, and sensor failures. One major hurdle has been the lack of real-world datasets. This paper presents a pioneering and comprehensive real-world multi-robot collaborative perception dataset to boost research in this area. Our dataset leverages the untapped potential of air-ground robot collaboration featuring distinct spatial viewpoints, complementary robot mobilities, coverage ranges, and sensor modalities. It features raw sensor inputs, pose estimation, and optional high-level perception annotation, thus accommodating diverse research interests. Compared to existing datasets predominantly designed for Simultaneous Localization and Mapping (SLAM), our setup ensures a diverse range and adequate overlap of sensor views to facilitate the study of multi-robot collaborative perception algorithms. We demonstrate the value of this dataset qualitatively through multiple collaborative perception tasks. We believe this work will unlock the potential research of high-level scene understanding through multi-modal collaborative perception in multi-robot settings. Copyright © 2024, The Authors. All rights reserved.

关键词： Multipurpose robots

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Meeting report of the seventh annual Tri-Service Microbiome Consortium Symposium

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BMC Proceedings 2024年第SUPPL 20期18卷 1-9页

作者： Liechty, Zachary S. Agans, Richard T. Barbato, Robyn A. Colston, Sophie M. Christian, Monica R. Hammamieh, Rasha Kardish, Melissa R. Karl, J. Philip Leary, Dagmar H. Mauzy, Camilla A. de Goodfellow, Ida Pantoja-Feliciano Racicot, Kenneth Soares, Jason W. Stamps, Blake W. Sweet, Charles R. Tuck, Sara M. Whitman, Jordan A. Goodson, Michael S. 711th Human Performance Wing Air Force Research Laboratory Wright‐Patterson AFB Dayton OH United States United States Army ERDC Cold Regions Research and Engineering Laboratory Hanover NH United States United States Naval Research Laboratory Washington DC United States Medical Readiness Systems Biology Walter Reed Army Institute of Research Silver Spring MD United States Military Nutrition Division United States Army Research Institute of Environmental Medicine Natick MA United States Soldier Effectiveness Directorate United States Army Combat Capabilities Development Command Soldier Center Natick MA United States Unites States Naval Academy Annapolis MD United States

The Tri-Service Microbiome Consortium (TSMC) was founded to enhance collaboration, coordination, and communication of microbiome research among DoD organizations and to facilitate resource, material and information sharing among consortium members, which includes collaborators in academia and industry. The 2023 annual symposium was a hybrid meeting held in Washington DC on 26–27 September 2023 concurrent with the virtual attendance, with oral and poster presentations and discussions centered on microbiome-related topics within five broad thematic areas: 1) Environmental Microbiome Characterization;2) Microbiome Analysis;3) Human Microbiome Characterization;4) Microbiome engineering;and 5) In Vitro and In Vivo Microbiome Models. Collectively, the symposium provided an update on the scope of current DoD and DoD-affiliated microbiome research efforts and fostered collaborative opportunities. This report summarizes the presentations and outcomes of the 7th annual TSMC symposium. © This is a U.S. Government work and not under copyright protection in the US;foreign copyright protection may apply 2024.

关键词： Environmental Microbiome Human Microbiome Microbiome engineering Military Microbiome Model Microbiome Systems

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Examining Surface-Wetting and Leidenfrost Transition of Jet Fuels and Bicomponent Mixtures

SSRN

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SSRN 2023年

作者： Werner, Ryan Mayhew, Eric Kim, Kenneth Kweon, Chol-Bum Michael, James B. Department of Mechanical Engineering Iowa State University AmesIA50011 United States Combat Capabilities Development Command's Army Research Laboratory United States US Army Research Laboratory United States

The regime during droplet impact with high temperature walls is important for understanding the generation of fuel vapor and the potential production of pollutants. Experimental data on regime behavior and associated surface contact, which is closely linked with the heat transfer of the event are needed to validate models and simulations focused on vaporization behavior. This paper outlines dual-view imaging experiments that examine surface contact and corresponding regime behavior for single component, bicomponent, and both petroleum distillate and sustainable aviation fuels for impact Weber numbers from 15–550 and temperatures between 500 and 700 K to encompass a variety of behaviors for each fluid studied. Trials were classified into one of three categories: full contact, transition, or Leidenfrost behavior. Transition cases included partial wetting, finger boiling, and a distinct "prompt" Leidenfrost behavior. Results are compared using the Stefan number for regime classification, and a paired nondimensional heat flux and residence time were better suited to predicting regime boundaries. Two-parameter empirical correlations for n-decane, n-dodecane, bicomponent mixtures, and real fuels F-24 and ATJ are defined for the onset of the Leidenfrost boundary. This data and correlations will be used to help validate and verify numerical simulations of spray-wall interactions. © 2023, The Authors. All rights reserved.

关键词： Wetting

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Deep Linearization Mappings for Canonical Correlation Clustering

Deep Linearization Mappings for Canonical Correlation Cluste...

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Asilomar Conference on Signals, Systems & Computers

作者： Akshay Malhotra Ioannis D. Schizas João Morais InterDigital Communications Los Altos CA USA US Army Combat Capabilities Development Command US Army Research Laboratory MD USA School of Electrical Computer and Energy Engineering at Arizona State University Tempe AZ USA

ISBN: (数字)9798350354058

ISBN: (纸本)9798350354065

Kernelized canonical correlations analysis has been utilized as a means to carry out unsupervised data clustering. This work puts forth a method to obtain a non-linear mapping that transforms data to a feature space where the data has the potential to be more ‘linearly’ correlated. An auto encoder network is employed to minimize a reconstruction error and learn a proper non-linear mapping to transform the input data. The non-linear mapping found via the novel scheme goes beyond kernel functions and results in better clustering performance than linear and kernel-based canonical correlations as demonstrated by numerical tests conducted across two different data sets.

关键词： Computers Correlation Transforms Kernel Standards

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Data Fusion of Deep Learned Molecular Embeddings for Property Prediction

arXiv

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arXiv 2025年

作者： Appleton, Robert J. Barnes, Brian C. Strachan, Alejandro School of Materials Engineering Birck Nanotechnology Center Purdue University West LafayetteIN47907 United States U.S. Army Combat Capabilities Development Command Army Research Laboratory Aberdeen Proving Ground MD21005 United States

Data-driven approaches such as deep learning can result in predictive models for material properties with exceptional accuracy and efficiency. However, in many problems data is sparse, severely limiting their accuracy and applicability. To improve predictions, techniques such as transfer learning and multi-task learning have been used. The performance of multi-task learning models depends on the strength of the underlying correlations between tasks and the completeness of the dataset. We find that standard multi-task models tend to underperform when trained on sparse datasets with weakly correlated properties. To address this gap, we use data fusion techniques to combine the learned molecular embeddings of various single-task models and trained a multi-task model on this combined embedding. We apply this technique to a widely used benchmark dataset of quantum chemistry data for small molecules as well as a newly compiled sparse dataset of experimental data collected from literature and our own quantum chemistry and thermochemical calculations. The results show that the fused, multi-task models outperform standard multi-task models for sparse datasets and can provide enhanced prediction on data-limited properties compared to single-task models. © 2025, CC BY.

关键词： Image fusion

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Optimal Link Configuration for Covert Heterogeneous Wireless Networks with Power Constraints

Optimal Link Configuration for Covert Heterogeneous Wireless...

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Annual Conference on Information Sciences and Systems (CISS)

作者： Amna Gillani Beatriz Lorenzo Majid Ghaderi Fikadu Dagefu Dennis Goeckel Department of Electrical and Computer Engineering University of Massachusetts Amherst Amherst MA USA Department of Computer Science University of Calgary Calgary Canada U.S. Army Combat Capabilities Development Command (DEVCOM) Army Research Laboratory Adelphi MD USA

ISBN: (数字)9798331513269

ISBN: (纸本)9798331513276

Heterogeneous Networks (HetNets) leverage multiple communication interfaces (e.g., Wi-Fi, cellular, Bluetooth) seamlessly integrated to enhance connectivity and capacity across diverse environments. These capabilities can be advantageous for covert communication, where the objective is to ensure undetectable transmission in the presence of an adversary. This work investigates optimal power allocation strategies for covert communication within HetNets under maximum power constraints. We propose a polynomial-time (m 2 ) algorithm for optimal link configuration by allocating power across multiple modes. Next, we address network-level covertness by allocating the end-to-end covertness constraint across links in a two-hop system that maximizes throughput. Leveraging the link configuration approach, we derive the optimal power allocation for each mode and link, ensuring the overall transmission remains undetectable. Numerical results demonstrate that the proposed method outperforms existing single-link and two-hop approaches, achieving higher efficiency and security in covert communication across HetNets.

关键词： Wireless networks Heuristic algorithms Interference Throughput Robustness Heterogeneous networks Topology Resource management Security Wireless fidelity

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Profiled-Truncation Technique for Busemann-Traced Compression Fields

SSRN

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SSRN 2025年

作者： Kang, Kyungrae Kato, Nozomu D’Agostino, Mitchel Lee, Gyu Sub Mayhew, Eric Lee, Tonghun Mechanical Science and Engineering University of Illinois at Urbana-Champaign 1206 W. Green Street UrbanaIL61801 United States Combat Capabilities Development Command's Army Research Laboratory Aberdeen Proving GroundMD21005 United States

A novel technique for balancing a high-speed air intake's overall length and total pressure recovery using streamline-tracing via profiled truncation is developed and demonstrated numerically. This profiling prescribes an azimuthally dependent truncation angle distribution along the stream-traced leading edge mitigating excessive length of the untruncated designs with minimal flow distortions and total pressure losses. Among various capture shapes, a scoop-type was chosen to examine the proposed technique. Various correction methods were performed to curtail the length while retaining a comparable flow characteristic to the reference scoop, allowing distinct wall profiles depending on the parameterization. With inviscid analyses, the resultant flow fields showed a comparable static pressure rise at a 25% reduced length while reducing the total pressure recovery by only 3%. In viscous simulations where the reductions of the length and area are more critical, the profile-truncated scoops yielded even higher total pressure recovery by 26% with an increased mass capture rate by 1.6%. The resultant boundary-layer thickness and the effect of non-zero gradient in the circumferential direction were discussed to verify the proposed method. © 2025, The Authors. All rights reserved.

关键词： Computational fluid dynamics

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