Results for “Complex industrial process” — Page 56

DOE OSTI2025

Insight into industrial hemp ( Cannabis sativa L.) root exudation composition in a simulated soil environment: a rhizosphere-on-a-chip study

Microfluidic technologies provide a reduced complexity and soil-free environment to study plant-soil interactions at the microscale. Traditionally used for model plants such as Arabidopsis thaliana, this study represents the first application of a rhizosphere-on-a-chip (RhizoChip) to investigate root exudation in industrial hemp (Cannabis sativa L.), an agronomic crop with growing economic importance. By incorporating soil-like minerals (kaolinite, potassium feldspar, and biotite), the RhizoChip addresses limitations of previous research. Hemp seedlings grown in mineral-containing chips exhibited significant root growth, emphasizing the critical role of minerals in root development. Using untargeted metabolomics, 170 compounds were identified, including organic acids, amino acids, and secondary metabolites, with distinct profiles across conditions. Metabolic pathway analysis revealed activity in amino acid metabolism, the citric acid cycle, and secondary metabolite biosynthesis. In conclusion, this study highlights the RhizoChip's potential for long-term studies of root exudates in non-model crops and offers insights into rhizosphere processes with implications for sustainable agriculture.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

A Multidisciplinary Approach to Integrated Energy Systems: Advanced Nuclear Plants with Thermal Storage for Dynamic and Flexible Operation in Diverse Markets

Energy supply, distribution, and demand are continuously evolving in accordance with the integration of new power generation sources. In the United States, there is a progressive shift toward incorporating fluctuating energy sources such as wind and solar into the energy mix, alongside the distributed generation. Simultaneously, we are seeing a revolution in consumer technologies such as electric vehicles, energy devices for both residential and commercial use, and industrial processes—all contributing to a fundamental change in energy consumption dynamics. These scenarios have led to huge demand for enhanced flexibility from nuclear power plants (NPPs), requiring them to operate with unprecedented adaptability. Furthermore, advanced NPPs (A-NPPs) could potentially apply to scenarios in which power generation flexibility is prioritized over its current and conventional baseload generation capacity for traditional demand patterns. The present work covers several configurations for coupling nuclear energy production with thermal energy storage (TES). Previous work evaluated systems entailing a simple nuclear-TES configuration that used steam as a heat source for the TES of three different advanced reactors (ARs), but its heat diversion ratio (HDR) for charging was limited. The present work proposes a new configuration that features full decoupling of the nuclear reactor and the power cycle, using reactor coolant (i.e., gas) as a heat source for the TES and offering a theoretically unlimited HDR. This configuration is, however, more complex, as both high- and low-temperature TES (HT-TES and LT-TES) systems are required in order to cover the extended temperature range. Although this configuration imposes certain limitations on the discharge system configuration, it also presents the opportunity to design a more efficient system. For this case in particular, a steam reheat cycle is advantageous. Conventional TES systems take advantage of nominal efficiency when discharging, whereas the reheat cycle in the fully decoupled TES system affords a significant efficiency increase over conventional cases. Material selection, component/equipment sizing, and costing analyses were performed, followed by economic dispatch and size optimization. Dynamic models were developed for the decoupled system in order to generate insights into aspects of off design operation (e.g., drops in cycle efficiency), and these models enable exploration of potential mitigation strategies for addressing such drops. The models also highlight the need to design fail-safes that ensure continuous operational stability and minimize the impact of power ramping on the reactor parameters.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2017

Characteristics of Non-metallic Inclusions in Steel Obtained from Different-Sized Samplers

To determine the effect of sampler size on the detection of inclusions in liquid steel, four different-sized samplers were designed for industrial sampling from a continuous casting tundish. The samples were evaluated via scanning electron microscopy and energy-dispersive spectroscopy. With increasing sample size, the cooling rate of the sample and velocity for particle engulfment decreased. The extent of encapsulation of complex inclusions increased from 0 pct with the smallest sampler to 48.2 pct with the largest sampler. In the samplers that cooled at 41.2 and 26.7 K s{sup −1}, the major inclusions were calcium aluminates; in the larger samplers, which cooled more slowly at 8.2 and 1.0 K s{sup −1}, the complex inclusions predominately comprised Al{sub 2}O{sub 3} + (Ca, Mn)S and Al{sub 2}O{sub 3} + CaS, respectively. The sizes of the sulfides gradually increased with increasing sampler size; for example, the sulfide average diameter increased from 2.5 to 3.5 μm when the sampler inner diameter increased from 50 to 70 mm. The main direction of movement of the inclusions during the sampling process was upward.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Multiscale geographically and temporally weighted regression (MGTWR): exploring the spatiotemporal heterogeneity of EV market adoption

As an innovative vehicle technology, electric vehicles are experiencing growing sales and have made significant inroads into the traditional automotive market in the United States and around the world. However, EV adoption rates vary significantly across space and over time, influenced by a complex interplay of socio-economic and infrastructural factors alongside federal and state policies. Here, this paper presents a comprehensive spatial–temporal investigation of EV market adoption within one city in the US, that of Chicago, utilizing Multiscale Geographically and Temporally Weighted Regression (MGTWR) alongside Multiscale Geographically Weighted Regression (MGWR). The aim is to unravel the spatial and temporal dynamics affecting EV adoption and to explore how the influence of various determinants of EV adoption, such as demographic factors and economic conditions, vary spatially. Moreover, by utilizing MGTWR, we provide insights into the evolution of these relationships over time, offering a predictive outlook on future EV market growth. Our findings, with an 86.6% prediction accuracy for EV market adoption, tailored policy measures to support accelerated EV adoption. Methodologically, this work advances MGWR frameworks by integrating temporal dynamics to examine nonstationary processes in spatially disaggregated contexts. These findings offer evidence–based guidance for policymakers, urban planners, and stakeholders in the automotive industry, supporting the transition toward a more sustainable and efficient transportation system.

EV Market Adoption↗

NASA NTRS1993

New monomers for high performance polymers

This laboratory has been concerned with the development of new polymeric materials with high thermo-oxidative stability for use in the aerospace and electronics industries. Currently, there is special emphasis on developing matrix resins and composites for the high speed civil transport (HSCT) program. This application requires polymers that have service lifetimes of 60,000 hr at 350 F (177 C) and that are readily processible into void-free composites, preferably by melt-flow or powder techniques that avoid the use of high boiling solvents. Recent work has focused on copolymers which have thermally stable imide groups separated by flexible arylene ether linkages, some with trifluoromethyl groups attached to the aromatic rings. The presence of trifluoromethyl groups in monomers and polymers often improves their solubility and processibility. The goal of this research was to synthesize several new monomers containing pendant trifluoromethyl groups and to incorporate these monomers into new imide/arylene ether copolymers. Initially, work was begun on the synthesis of three target compounds. The first two, 3,5-dihydroxybenzo trifluoride and 3-amino 5-hydroxybenzo trifluoride, are intermediates in the synthesis of more complex monomers. The third, 3,5-bis (3-amino-phenoxy) benzotrifluoride, is an interesting diamine that could be incorporated into a polyimide directly.

Gratz, Roy F.↗

NASA NTRS2009

Device for Measuring Low Flow Speed in a Duct

A multiple-throat venturi system has been invented for measuring laminar flow of air or other gas at low speed (1 to 30 cm/s) in a duct while preserving the laminar nature of the flow and keeping the velocity profile across the duct as nearly flat as possible. While means for measuring flows at higher speeds are well established, heretofore, there have been no reliable means for making consistent, accurate measurements in this speed range. In the original application for which this system was invented, the duct leads into the test section of a low-speed wind tunnel wherein uniform, low-speed, laminar flow is required for scientific experiments. The system could also be used to monitor a slow flow of gas in an industrial process like chemical vapor deposition. In the original application, the multiple- throat venturi system is mounted at the inlet end of the duct having a rectangular cross section of 19 by 14 cm, just upstream of an assembly of inlet screens and flow straighteners that help to suppress undesired flow fluctuations (see Figure 1). The basic venturi measurement principle is well established: One measures the difference in pressure between (1) a point just outside the inlet, where the pressure is highest and the kinetic energy lowest; and (2) the narrowest part (the throat) of the venturi passage, where the kinetic energy is highest and the pressure is lowest. Then by use of Bernoulli s equation for the relationship between pressure and kinetic energy, the volumetric flow speed in the duct can be calculated from the pressure difference and the inlet and throat widths. The design of this system represents a compromise among length, pressure recovery, uniformity of flow, and complexity of assembly. Traditionally, venturis are used to measure faster flows in narrower cross sections, with longer upstream and downstream passages to maintain accuracy. The dimensions of the passages of the present venturi system are sized to provide a readily measurable pressure drop. Multiple throats are used to minimize the length needed to recover internal energy and enable the velocity profile to recover to near flatness.

Quinn, Frank↗

NASA NTRS2009

Measuring Thermal Conductivity of a Small Insulation Sample

A multiple-throat venturi system has been invented for measuring laminar flow of air or other gas at low speed (1 to 30 cm/s) in a duct while preserving the laminar nature of the flow and keeping the velocity profile across the duct as nearly flat as possible. While means for measuring flows at higher speeds are well established, heretofore, there have been no reliable means for making consistent, accurate measurements in this speed range. In the original application for which this system was invented, the duct leads into the test section of a low-speed wind tunnel wherein uniform, low-speed, laminar flow is required for scientific experiments. The system could also be used to monitor a slow flow of gas in an industrial process like chemical vapor deposition. In the original application, the multiple- throat venturi system is mounted at the inlet end of the duct having a rectangular cross section of 19 by 14 cm, just upstream of an assembly of inlet screens and flow straighteners that help to suppress undesired flow fluctuations (see Figure 1). The basic venturi measurement principle is well established: One measures the difference in pressure between (1) a point just outside the inlet, where the pressure is highest and the kinetic energy lowest; and (2) the narrowest part (the throat) of the venturi passage, where the kinetic energy is highest and the pressure is lowest. Then by use of Bernoulli s equation for the relationship between pressure and kinetic energy, the volumetric flow speed in the duct can be calculated from the pressure difference and the inlet and throat widths. The design of this system represents a compromise among length, pressure recovery, uniformity of flow, and complexity of assembly. Traditionally, venturis are used to measure faster flows in narrower cross sections, with longer upstream and downstream passages to maintain accuracy. The dimensions of the passages of the present venturi system are sized to provide a readily measurable pressure drop. Multiple throats are used to minimize the length needed to recover internal energy and enable the velocity profile to recover to near flatness.

Miller, Robert A.↗

NASA NTRS2012

SE-FIT

The mathematical theory of capillary surfaces has developed steadily over the centuries, but it was not until the last few decades that new technologies have put a more urgent demand on a substantially more qualitative and quantitative understanding of phenomena relating to capillarity in general. So far, the new theory development successfully predicts the behavior of capillary surfaces for special cases. However, an efficient quantitative mathematical prediction of capillary phenomena related to the shape and stability of geometrically complex equilibrium capillary surfaces remains a significant challenge. As one of many numerical tools, the open-source Surface Evolver (SE) algorithm has played an important role over the last two decades. The current effort was undertaken to provide a front-end to enhance the accessibility of SE for the purposes of design and analysis. Like SE, the new code is open-source and will remain under development for the foreseeable future. The ultimate goal of the current Surface Evolver Fluid Interface Tool (SEFIT) development is to build a fully integrated front-end with a set of graphical user interface (GUI) elements. Such a front-end enables the access to functionalities that are developed along with the GUIs to deal with pre-processing, convergence computation operation, and post-processing. In other words, SE-FIT is not just a GUI front-end, but an integrated environment that can perform sophisticated computational tasks, e.g. importing industry standard file formats and employing parameter sweep functions, which are both lacking in SE, and require minimal interaction by the user. These functions are created using a mixture of Visual Basic and the SE script language. These form the foundation for a high-performance front-end that substantially simplifies use without sacrificing the proven capabilities of SE. The real power of SE-FIT lies in its automated pre-processing, pre-defined geometries, convergence computation operation, computational diagnostic tools, and crash-handling capabilities to sustain extensive computations. SE-FIT performance is enabled by its so-called file-layer mechanism. During the early stages of SE-FIT development, it became necessary to modify the original SE code to enable capabilities required for an enhanced and synchronized communication. To this end, a file-layer was created that serves as a command buffer to ensure a continuous and sequential execution of commands sent from the front-end to SE. It also establishes a proper means for handling crashes. The file layer logs input commands and SE output; it also supports user interruption requests, back and forward operation (i.e. undo and redo), and others. It especially enables the batch mode computation of a series of equilibrium surfaces and the searching of critical parameter values in studying the stability of capillary surfaces. In this way, the modified SE significantly extends the capabilities of the original SE.

Chen, Yongkang↗

DOE OSTI2017

Development of a Dynamic Lidar Uncertainty Framework

As wind turbine sizes increase and wind energy expands to more complex and remote sites, remote-sensing devices such as lidars are expected to play a key role in wind resource assessment and power performance testing. The switch to remote-sensing devices represents a paradigm shift in the way the wind industry typically obtains and interprets measurement data for wind energy. For example, the measurement techniques and sources of uncertainty for a remote-sensing device are vastly different from those associated with a cup anemometer on a meteorological tower. Current IEC standards for quantifying remote sensing device uncertainty for power performance testing consider uncertainty due to mounting, calibration, and classification of the remote sensing device, among other parameters. Values of the uncertainty are typically given as a function of the mean wind speed measured by a reference device and are generally fixed, leading to climatic uncertainty values that apply to the entire measurement campaign. However, real-world experience and a consideration of the fundamentals of the measurement process have shown that lidar performance is highly dependent on atmospheric conditions, such as wind shear, turbulence, and aerosol content. At present, these conditions are not directly incorporated into the estimated uncertainty of a lidar device. In this presentation, we describe the development of a new dynamic lidar uncertainty framework that adapts to current flow conditions and more accurately represents the actual uncertainty inherent in lidar measurements under different conditions. In this new framework, sources of uncertainty are identified for estimation of the line-of-sight wind speed and reconstruction of the three-dimensional wind field. These sources are then related to physical processes caused by the atmosphere and lidar operating conditions. The framework is applied to lidar data from a field measurement site to assess the ability of the framework to predict errors in lidar-measured wind speed. The results show how uncertainty varies over time and can be used to help select data with different levels of uncertainty for different applications, for example, low uncertainty data for power performance testing versus all data for plant performance monitoring.

17 WIND ENERGY↗

DOE OSTI2021

Opportunities and Challenges of Lignin Utilization

Lignin is the most abundant non-carbohydrate component of plant cell walls and the largest aromatic source on earth. It is gaining more attention due to its potentials for many industrial applications. Compared to the applications of carbohydrate components like cellulose and hemicellulose, the utilization of lignin is challenging due to its natural rigidity, heterogeneity, and complexity. On the other hand, the successful utilization of lignin can broaden the spectrum of renewable resources in producing chemicals, fuels, and materials. In addition, value-added lignin products can enhance the economic competitivity of many biofuels and biochemicals mainly produced from cellulose and hemicellulose. In the last few decades, there have been notable improvements in fundamental understandings of the plant cell wall, lignin chemistry, catalysis, and other engineering principles, as well as the development of diverse conversion and characterization technologies. Prior to the detailed discussions of recent lignin utilization strategies through decomposition approaches such as thermochemical, biological, photoelectrochemical and electrochemical depolymerization and material approaches including carbon materials, adsorbents, thermosets, thermoplastics, hydrogels and nanoparticles, this chapter briefly discusses the types of lignin and its potentials and limitations based on its characteristics and applied processes.

Geun yoo, Chang↗

DOE OSTI2015

Study of treatment as an alternative WM pathway: examples of I-graphite and metallic components such as steam generators - 15212

EDF is working continuously to optimize and secure its waste management pathways, leading in some case to develop appropriate treatment solutions that could be implemented parallel to reference solutions, complementary or as alternative solutions to already existing paths. This approach is illustrated by the examples of steam generators replaced during the operation of French PWR power plants, and of irradiated graphite (stacks and sleeves), coming from the decommissioning of UNGG reactors, which have been shut down. Concerning graphite wastes, the near surface disposal facility intended for this waste does not exist yet, and is currently giving rise to the research of a suitable site, and an evaluation of its performances. While accompanying ANDRA (French national agency for nuclear waste management), in charge of the development of the facility, and while waiting for more data to be available, EDF is continuing the consolidation of graphite wastes radiological inventory, and is working on the development of an alternative management solution, based on a thermal treatment process. Depending on the nature of the treatment, and on the choice of operating parameters, this treatment may contribute to reduce graphite wastes volume and/or promote its acceptance in a disposal facility. Reducing the radiological inventory by decontamination is one of the means to achieve these objectives. Concerning replaced steam generators, nearly 200 of them will have been removed by 2030, and stored on site waiting for their treatment, which represents about 65 000 tons of metal. Initially intended to be cut and packed on NPPs' sites during their dismantling, EDF is studying the economic value of having the steam generators treated in a centralized facility, which allows reducing the volume of final wastes by optimizing cutting operations, while considering recycling after melting. However, this studied pathway implies a number of difficulties to be overcome. In particular, the shipment of such large components to a centralized facility may be complex. Moreover, French regulatory framework does not allow recycling outside nuclear industry, therefore limiting recycling opportunities to storage containers for radioactive wastes. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2016

Importance Ranking of Software Dependability Attributes in the Nuclear Industry

With the current transition from analog to digital instrumentation and control systems in nuclear power plants, the number and variety of software-based systems has significantly increased. Due to the sophisticated nature and the increasing complexity of software, a significant challenge faced by the nuclear industry is the trust one can place in software-based systems once they have been developed. The trust placed in software is typically termed software dependability, a qualifier which encompasses different attributes such as software reliability, safety, security, availability and maintainability. It is recognized that these attributes relate to each other in different ways under various scenarios. The detailed dependencies between software dependability attributes can be found in a previous study. With limited time and budget resources, which dependability attribute should be given the highest priority when certifying software-based systems in the nuclear industry is a fundamental question that needs to be answered. This paper addresses this problem using stakeholders' opinion elicitation. A comprehensive questionnaire was designed to elicit the goals that should be fulfilled by the nuclear industry and to collect the relative importance of the various dependability attributes for each goal. We then used the Analytical Hierarchy Process (AHP) to analyze the data and obtained the relative importance ranking of software dependability attributes in the context of a reactor protection system. The results will provide guidance to resource allocation for the certification of software dependability in the nuclear industry. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

Imaging of a fluid injection process using geophysical data — A didactic example

In many subsurface industrial applications, fluids are injected into or withdrawn from a geologic formation. It is of practical interest to quantify precisely where, when, and by how much the injected fluid alters the state of the subsurface. Routine geophysical monitoring of such processes attempts to image the way that geophysical properties, such as seismic velocities or electrical conductivity, change through time and space and to then make qualitative inferences as to where the injected fluid has migrated. The more rigorous formulation of the time-lapse geophysical inverse problem forecasts how the subsurface evolves during the course of a fluid-injection application. Using time-lapse geophysical signals as the data to be matched, the model unknowns to be estimated are the multiphysics forward-modeling parameters controlling the fluid-injection process. Properly reproducing the geophysical signature of the flow process, subsequent simulations can predict the fluid migration and alteration in the subsurface. The dynamic nature of fluid-injection processes renders imaging problems more complex than conventional geophysical imaging for static targets. This work intents to clarify the related hydrogeophysical parameter estimation concepts.

58 GEOSCIENCES↗

DOE OSTI2022

Smart connected worker edge platform for smart manufacturing: Part 1—Architecture and platform design

Abstract The challenge of sustainably producing goods and services for healthy living on a healthy planet requires simultaneous consideration of economic, societal, and environmental dimensions in manufacturing. Enabling technology for data driven manufacturing paradigms like Smart Manufacturing (a.k.a. Industry 4.0) serve as the technological backbone from which sustainable approaches to manufacturing can be implemented. Unfortunately, these technologies are typically associated with broader and deeper factory automation that is often too expensive and complex for the small and medium sized manufacturers (SMMs) that comprise the majority of manufacturing business in the USA and for whom their most valuable asset are the people whose jobs automation while replace. This paper describes an edge intelligent platform to integrate internet‐of‐things technologies with computing hardware, software, computational workflows for machine learning, and data ingestion, enabling SMMs to transition into smart manufacturing paradigms by leveraging the intelligence of their people. The platform leverages consumer grade electronics and sensors (affordable and portable), customized software with open source software packages (accessible), and existing communication network infrastructures (scalable). The software systems are implemented via Kubernetes orchestration of Docker containerization to ensure scalability and programmability. The platform is adaptive via computational workflow engines that produce information from data by processing with low‐cost edge computing devices while efficiently accessing resources of cloud servers as needed. The proposed edge platform connects workers to technological resources that provide computational intelligence (i.e., silicon‐based sensing and computation for data collection and contextualization) to enable decision making at the edge of advanced manufacturing.

Kim, Yoon G.↗

NASA NTRS1994

Infinite possibilities: Computational structures technology

Computational Fluid Dynamics (or CFD) methods are very familiar to the research community. Even the general public has had some exposure to CFD images, primarily through the news media. However, very little attention has been paid to CST--Computational Structures Technology. Yet, no important design can be completed without it. During the first half of this century, researchers only dreamed of designing and building structures on a computer. Today their dreams have become practical realities as computational methods are used in all phases of design, fabrication and testing of engineering systems. Increasingly complex structures can now be built in even shorter periods of time. Over the past four decades, computer technology has been developing, and early finite element methods have grown from small in-house programs to numerous commercial software programs. When coupled with advanced computing systems, they help engineers make dramatic leaps in designing and testing concepts. The goals of CST include: predicting how a structure will behave under actual operating conditions; designing and complementing other experiments conducted on a structure; investigating microstructural damage or chaotic, unpredictable behavior; helping material developers in improving material systems; and being a useful tool in design systems optimization and sensitivity techniques. Applying CST to a structure problem requires five steps: (1) observe the specific problem; (2) develop a computational model for numerical simulation; (3) develop and assemble software and hardware for running the codes; (4) post-process and interpret the results; and (5) use the model to analyze and design the actual structure. Researchers in both industry and academia continue to make significant contributions to advance this technology with improvements in software, collaborative computing environments and supercomputing systems. As these environments and systems evolve, computational structures technology will evolve. By using CST in the design and operation of future structures systems, engineers will have a better understanding of how a system responds and lasts, more cost-effective methods of designing and testing models, and improved productivity. For informational and educational purposes, a videotape is being produced using both static and dynamic images from research institutions, software and hardware companies, private individuals, and historical photographs and drawings. The extensive number of CST resources indicates its widespread use. Applications run the gamut from simpler university-simulated problems to those requiring solutions on supercomputers. In some cases, an image or an animation will be mapped onto the actual structure to show the relevance of the computer model to the structure. Transferring the digital files to videotape presents a number of problems related to maintaining the quality of the original image, while still producing a broadcast quality videotape. Since researchers normally do not create a computer image using traditional composition theories or video production requirements, often the image loses some of its original digital quality and impact when transferred to videotape. Although many CST images are currently available, those that are edited into the final project must meet two important criteria: they must complement the narration, and they must be broadcast quality when recorded on videotape.

Beam, Sherilee F.↗

NASA NTRS2020

Julia Programming Language Benchmark Using a Flight Simulation

Julia’s goal to provide scripting language ease-of-coding with compiled language speed is explored. The runtime speed of the relatively new Julia programming language is assessed against other commonly used languages including Python, Java, and C++. An industry-standard missile and rocket simulation, coded in multiple languages, was used as a test bench for runtime speed. All language versions of the simulation, including Julia, were coded to a highly-developed object-oriented simulation architecture tailored specifically for time-domain flight simulation. A “speed-of-coding” second-dimension is plotted against runtime for each language to portray a space that characterizes Julia’s scripting language efficiencies in the context of the other languages. With caveats, Julia runtime speed was found to be in the class of compiled or semi-compiled languages. However, some factors that affect runtime speed at the cost of ease-of-coding are shown. Julia’s built-in functionality for multi-core processing is briefly examined as a means for obtaining even faster runtime speed. The major contribution of this research to the extensive language benchmarking body-of-work is comparing Julia to other mainstream languages using a complex flight simulation as opposed to benchmarking with single algorithms.

Sells, Ray↗

NASA NTRSDate not supplied

Feasibility Study of Distributed Decision-Making on the Edge for Urban Air Mobility

The Concept of Operations for Urban Air Mobility (UAM) put forward by FAA, NASA, and several industry stakeholders acknowledges the diversity and complexity in UAM operations and, thereby, envisions a federated architecture for UAM management. In this architecture, the decision-making is distributed to a set of service providers who collectively manage the shared airspace usage by different stakeholders. This notionally brings autonomy closer to the UAM businesses and encourages to explore the feasibility of decision making on the very edge, which is the topic of the presented research. This paper reports research conducted on the hypothesis based on which the residual compute capability onboard smart unmanned aerial systems (UASs) is utilized to build situational awareness and resolve conflicts by passive and active coordination among multiple UASs, thereby implementing a layer of distributed autonomy in UAM. Key features of the edge-computing approach involve inter-UAS information exchange, independent assessment of own flight and environmental conditions, and estimation of other UASs’ flight preferences, incorporating machine learning techniques in the last two. Parallel computing on portable graphics processing unit (GPU) enables the machine learning workflow on the edge. A custom-built 3D simulator is used to evaluate the efficacy of the distributed decision-making on the edge. Each edge node, representing a smart UAS, connects to the simulator from a remote location and independently controls the behavior of the corresponding virtual asset in the simulator, analogous to participants in an online multi-player game. The presented edge-computing-based distributed decision-making framework is envisioned to pave the way for collective mobility of autonomous air vehicles in the future shared airspace, while allowing the inclusion of the business preferences of the UAS operators within allowed regulatory limits.

Edge computing↗

NASA NTRSDate not supplied

Feasibility Study of Distributed Decision-Making on the Edge for Urban Air Mobility

The Concept of Operations for Urban Air Mobility (UAM) put forward by FAA, NASA, and several industry stakeholders acknowledges the diversity and complexity in UAM operations and, thereby, envisions a federated architecture for UAM management. In this architecture, the decision-making is distributed to a set of service providers who collectively manage the shared airspace usage by different stakeholders. This notionally brings autonomy closer to the UAM businesses and encourages to explore the feasibility of decision making on the very edge, which is the topic of the presented research. This paper reports research conducted on the hypothesis based on which the residual compute capability onboard smart unmanned aerial systems (UASs) is utilized to build situational awareness and resolve conflicts by passive and active coordination among multiple UASs, thereby implementing a layer of distributed autonomy in UAM. Key features of the edge-computing approach involve inter-UAS information exchange, independent assessment of own flight and environmental conditions, and estimation of other UASs’ flight preferences, incorporating machine learning techniques in the last two. Parallel computing on portable graphics processing unit (GPU) enables the machine learning workflow on the edge. A custom-built 3D simulator is used to evaluate the efficacy of the distributed decision-making on the edge. Each edge node, representing a smart UAS, connects to the simulator from a remote location and independently controls the behavior of the corresponding virtual asset in the simulator, analogous to participants in an online multi-player game. The presented edge-computing-based distributed decision-making framework is envisioned to pave the way for collective mobility of autonomous air vehicles in the future shared airspace, while allowing the inclusion of the business preferences of the UAS operators within allowed regulatory limits.

Edge computing↗