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At least 1,747 records · Page 97

Interdisciplinary Interactions During R&D and Early Design of Large Engineered Systems

Designing Large-Scale Complex Engineered Systems (LaCES) such as aircraft and submarines requires the input of thousands of engineers and scientists whose work is proximate in neither time nor space. Comprehensive knowledge of the system is dispersed among specialists whose expertise is in typically one system component or discipline. This study examined the interactive work practices among such specialists seeking to improve engineering practice through a rigorous and theoretical understanding of current practice. This research explored current interdisciplinary practices and perspectives during R&D and early LaCES design and identified why these practices and perspectives prevail and persist. The research design consisted of a three-fold, integrative approach that combined an open-ended survey, semi-structured interviews, and ethnography. Significant empirical data from experienced engineers and scientists in a large engineering organization were obtained and integrated with theories from organization science and engineering. Qualitative analysis was used to obtain a holistic, contextualized understanding. The over-arching finding is that issues related to cognition, organization, and social interrelations mostly dominate interactions across disciplines. Engineering issues, such as the integration of hardware or physics-based models, are not as significant. For example, organization culture is an important underlying factor that guided researchers more toward individual sovereignty over cross-disciplinarity. The organization structure and the engineered system architecture also serve as constraints to the engineering work. Many differences in work practices were observed, including frequency and depth of interactions, definition or co-construction of requirements, clarity or creation of the system architecture, work group proximity, and cognitive challenges. Practitioners are often unaware of these differences resulting in confusion and incorrect assumptions regarding work expectations. Cognitively, the enactment and coconstruction of knowledge are the fundamental tasks of the interdisciplinary interactions. Distributed and collective cognition represent most of the efforts. Argument, ignorance, learning, and creativity are interrelated aspects of the interactions that cause discomfort but yield benefits such as problem mitigation, broader understanding, and improved system design and performance. The quality and quantity of social interrelations are central to all work across disciplines with reciprocity, respectful engagement, and heedful interrelations being significant to the effectiveness of the engineering and scientific work.

McGowan, Anna-Maria Rivas↗

A Step-by-Step Protocol from METASPACE to Biological Interpretation

Mass spectrometry imaging (MSI) represents an exceptional tool for exploring complex biological systems spatially at the molecular level. However, due to its multidimensional nature and large-scale data output, it presents considerable challenges when it comes to extracting meaningful biological insights. Recent advancements, such as the METASPACE platform, have enabled researchers to efficiently process, annotate, and interpret MSI datasets by leveraging machine learning and cloud-based infrastructure. In this tutorial, we present a detailed and user-friendly R-pipeline designed to help METASPACE users navigate untargeted metabolomic annotations and transform them into practical insights about their biological systems. By combining METASPACE annotations with rapid R-based screening, this workflow not only streamlined the analytical process but also enhanced the understanding of spatial molecular distribution, especially for complex systems. Here, this easy-to-follow approach has the potential for applications in diagnostics, drug discovery, environmental and ecological processes, and more. We envision this pipeline to be particularly useful for newcomers to the field of MSI and

Moreno Pedraza, Abigail↗

Optimizing Mars Airplane Trajectory with the Application Navigation System

Planning complex missions requires a number of programs to be executed in concert. The Application Navigation System (ANS), developed in the NAS Division, can execute many interdependent programs in a distributed environment. We show that the ANS simplifies user effort and reduces time in optimization of the trajectory of a martian airplane. We use a software package, Cart3D, to evaluate trajectories and a shortest path algorithm to determine the optimal trajectory. ANS employs the GridScape to represent the dynamic state of the available computer resources. Then, ANS uses a scheduler to dynamically assign ready task to machine resources and the GridScape for tracking available resources and forecasting completion time of running tasks. We demonstrate system capability to schedule and run the trajectory optimization application with efficiency exceeding 60% on 64 processors.

Frumkin, Michael↗

Evaluation in context: ATC automation in the field

The process for incorporating advanced technologies into complex aviation systems is as important as the final product itself. This paper described a process that is currently being applied to the development and assessment of an advanced ATC automation system, CTAS. The key element of the process is field exposure early in the system development cycle. The process deviates from current established practices of system development -- where field testing is an implementation endpoint -- and has been deemed necessary by the FAA for streamlining development and bringing system functions to a level of stability and usefulness. Methods and approaches for field assessment are borrowed from human factors engineering, cognitive engineering, and usability engineering and are tailored for the constraints of an operational ATC environment. To date, the focus has been on the qualitative assessment of the match between TMA capabilities and the context for their use. Capturing the users' experience with the automation tool and understanding tool use in the context of the operational environment is important, not only for developing a tool that is an effective problem-solving instrument but also for defining meaningful operational requirements. Such requirements form the basis for certifying the safety and efficiency of the system. CTAS is the first U.S. advanced ATC automation system of its scope and complexity to undergo this field development and assessment process. With the rapid advances in aviation technologies and our limited understanding of their impact on system performance, it is time we opened our eyes to new possibilities for developing, validating, and ultimately certifying complex aviation systems.

Harwood, Kelly↗

On the Use of Resilience Models as Digital Twins for Operational Support and In time Decision Making

Human error is a major contributor to accidents and performance losses in complex engineered systems. If one examines these human error caused failures further, a specific cause, the lack of situation awareness, has dominated as a major cause of human errors that instigate latent or catastrophic failures in complex systems. Studies of aviation accidents involving major air carriers revealed that situation awareness was the root cause of around 90% of accidents involving pilot error. Another study explored offshore drilling accidents involving human error and found that 40% of accidents were directly attributed to the loss of situation awareness. Studies of human errors in other domains such as nuclear power, air traffic control, process industry, and advanced driving show that loss of SA was a root cause in a majority of the events. Situation awareness-related failures are not only common but also costly and fatal (e.g., Bhopal Gas Leak, Air France 447 Flight Crash). Thus, the concept of situation awareness has emerged as an important construct in human factors, resulting in numerous models and measurement methods to aid in promoting appropriate levels of situation awareness.

Lukman Irshad↗

Thermally-sustained structure in convectively unstable systems

The complex Ginzburg-Landau equation with a thermal noise term is studied under conditions when the system is convectively unstable. Under these conditions, the noise is selectively and spatially amplified giving rise to a noise-sustained structure. Analytical results, applicable to a wide range of physical systems, are derived for the variance, and the coefficients and thermal noise term are determined for Taylor-Couette flow with an axial through-flow. Comparison is made to recent experiments.

Deissler, Robert J.↗

A framework for calibrating and validating an air loop dynamic model in an HVAC system in Modelica

The use of Modelica for simulating the dynamic behaviors of building heating, ventilation, and air conditioning (HVAC) systems has gained popularity. Calibration of a model that represents large and complex HVAC systems in Modelica involves the determination of hundreds of parameters using real-world operation data. Considering the coupling effects among various components, such a calibration process is complex and time-consuming. In this study, we propose a systematic framework to efficiently calibrate and validate a complex HVAC system model in Modelica. The framework includes strategies to solicit real-system operation data and to decouple the model. The goal of this calibration framework is to accurately and efficiently determine a set of Modelica model parameters that provide a good match between the simulated and real system behaviors. To demonstrate the validity of the framework, it was applied to calibrate the parameters of a Modelica model of the air loop subsystem of a real AHU-VAV system. The results show that the calibrated model can generate simulated results, including VAV air flow rate, outdoor air flow, and fan power consumption, that match well with the operational data of the real system. The coefficient of the variation of the root mean square error, CV(RMSE), of the air flow rate and power consumption are 14.6 % and 11.5 %, respectively. The results prove that the framework is valid and effective, and it can be used to calibrate other complex HVAC system Modelica models in the future.

Li, Yicheng↗

Coupling a Computational Fluid Dynamics Model to a Spacecraft Thermal System Model for the DraMS Instrument Thermal Analysis

The Dragonfly Mass Spectrometer (DraMS) is an instrument on the Dragonfly mission, which will spend 7 years in deep space cruise before landing and operating on the surface of Titan. Vacuum thermal analyses are required for deep space cruise, and convection analyses are required for the Titan surface operations. Model exchanges across multiple thermal teams are needed for all phases of the mission. For DraMS, Thermal Desktop® (TD) has been the main thermal analytical tool of choice due to its capability in modeling complex thermal systems with relatively low computational power and for its availability across thermal teams. However, TD does not have computational fluid dynamics (CFD) capability and struggles to accurately capture complex convective behavior. DraMS has fans operating in tandem and gas flow behaviors are not easily predicted due to its complex flow paths. CFD software, such as Fluent, can model and predict such complex flow behaviors, but CFD models are computationally expensive, and its workflow processes are not tailored towards simulating large and complex systems. Therefore, a coupled modeling approach was chosen for DraMS: A TD model was used for simulating all the conductive, radiative, and source terms, while a Fluent CFD model was added on, as needed, to the TD model to provide the convective boundary conditions using the System Coupling software. The coupling software allows the TD and Fluent models to communicate data and arrive at a co-solved and co-converged solution. Furthermore, Thermal Iso-value Exchange (TIE) method was developed to facilitate and improve the TD-Fluent data exchange process. This paper will discuss the analytical studies that were done to verify the accuracy and usability of the coupled approach and the challenges associated, which lead to the development of the TIE approach. DraMS thermal design and co-solved analysis results will also be discussed.

Heat transfer↗

Coupling a Computational Fluid Dynamics (CFD) Model to a Spacecraft Thermal System Model for the DraMS Instrument Thermal Analysis

The Dragonfly Mass Spectrometer (DraMS) is an instrument on the Dragonfly mission, which will spend 7 years in deep space cruise before landing and operating on the surface of Titan. Vacuum thermal analyses are required for deep space cruise, and convection analyses are required for the Titan surface operations. Model exchanges across multiple thermal teams are needed for all phases of the mission. For DraMS, Thermal Desktop (TD) has been the main thermal analytical tool of choice due to its capability in modeling complex thermal systems with relatively low computational power and for its availability across thermal teams. However, TD does not have computational fluid dynamics (CFD) capability and struggles to accurately capture complex convective behavior. DraMS has fans operating in tandem and gas flow behaviors are not easily predicted due to its complex flow paths. CFD software, such as Fluent, can model and predict such complex flow behaviors, but CFD models are computationally expensive, and its workflow processes are not tailored towards simulating large and complex systems. Therefore, a coupled modeling approach was chosen for DraMS: A TD model was used for simulating all the conductive, radiative, and source terms, while a Fluent CFD model was added on, as needed, to the TD model to provide the convective boundary conditions using the System Coupling software. The coupling software allows the TD and Fluent models to communicate data and arrive at a co-solved and co-converged solution. Furthermore, Thermal Iso-value Exchange (TIE) method was developed to facilitate and improve the TD-Fluent data exchange process. This paper will discuss the analytical studies that were done to verify the accuracy and usability of the coupled approach and the challenges associated, which lead to the development of the TIE approach. DraMS thermal design and co-solved analysis results will also be discussed.

heat transfer↗

Radiation-induced transients on solid and molten Li and K iodides

The study, quantification, and monitoring of iodine in nuclear power generation systems have been paramount due to its environmental and health implications. Thorough speciation and transport studies strengthened the development and deployment of water reactors, which are now required for the new generation of Molten Salt Reactors (MSR), where the fuel and coolant are a complex liquid system of suitable halides. The speciation, radiation-induced chemistry, and transport of iodine (I-127, I-129 and I-131) under extreme conditions of temperature and ionizing radiation are among the challenges for the future implementation of MSR’s. In aqueous systems, the triiodide-iodine-iodide (I3--I2-I-) equilibrium is strongly dependent on the conditions of the medium. In molten iodides and chlorides, the triiodide detection (and its disproportionation) poses challenges due to the extreme conditions of temperature and radiation, but studies have shown a dependence on temperature, absorbed dose and salt composition. Through absorption spectroscopy techniques (diffuse reflectance and high-temperature UV-Vis), as well as resonance (Electron Paramagnetic Resonance) it is possible to identify primary transients induced by ionizing radiation trapped in the solid phase (Solid-state radiolysis), and steady-state main absorption components with a fast-acquisition real-time spectroscopy. The presence of heterogeneous phase (colloids), viscosity changes, and gas evolution are among the observed processes. A specific case of study is speciation in the presence of Ni. A corrosion product with magnetic properties due to unpaired electrons in its electronic structure. Ferromagnetic materials are monitored in solidified salts to identify aggregation and phase separation. Comparative studies of eutectic mixtures of LiI-KI and LiCl-KCl with known addition of dopants will be presented, with a perspective of radiation chemistry and its possible implications in complex systems.

36 - MATERIALS SCIENCE↗

Analysis of a fuel cell on-site integrated energy system for a residential complex

The energy use and costs of the on-site integrated energy system (OS/IES) which provides electric power from an on-site power plant and recovers heat that would normally be rejected to the environment is compared to a conventional system purchasing electricity from a utility and a phosphoric acid fuel cell powered system. The analysis showed that for a 500-unit apartment complex a fuel OS/IES would be about 10% more energy conservative in terms of total coal consumption than a diesel OS/IES system or a conventional system. The fuel cell OS/IES capital costs could be 30 to 55% greater than the diesel OS/IES capital costs for the same life cycle costs. The life cycle cost of a fuel cell OS/IES would be lower than that for a conventional system as long as the cost of electricity is greater than $0.05 to $0.065/kWh. An analysis of several parametric combinations of fuel cell power plant and state-of-art energy recovery systems and annual fuel requirement calculations for four locations were made. It was shown that OS/IES component choices are a major factor in fuel consumption, with the least efficient system using 25% more fuel than the most efficient. Central air conditioning and heat pumps result in minimum fuel consumption while individual air conditioning units increase it, and in general the fuel cell of highest electrical efficiency has the lowest fuel consumption.

Simons, S. N.↗

Formal Methods for Trusted Space Autonomy, Boon or Bane?

Trusted Space Autonomy is challenging in that space systems are complex artifacts deployed in a high stakes environment with complicated operational settings. Thus far these challenges have been met using the full arsenal of tools: formal methods, informal methods, testing, runtime techniques, and operations processes. Using examples from previous deployments of autonomy to the Remote Agent on DS-1, Autonomous Sciencecraft on EO-1, WATCH on MER, IPEX, AEGIS on MER, MSL, and M2020, and the M2020 Onboard planner, we discuss how each of these approaches have been used to enable successful deployment of autonomy. We next focus on relatively limited use of formal methods (both prior to deployment and runtime methods). From the needs perspective, formal methods represent the best chance for reliable autonomy as testing, informal methods, and operations accommodations do not scale well with increasing complexity of the autonomous system. However from the practice perspective, formal methods have been limited in their application due to difficulty in eliciting formal specifications and challenges in representing complex constraints such as metric time and resources. We discuss some of these challenges as well as the opportunity to extend formal and informal methods into runtime validation systems.

Chien, Steve↗

Machine Learning-Based Regression Models for Ironmaking Blast Furnace Automation

Computational fluid dynamics (CFD)-based simulation has been the traditional way to model complex industrial systems and processes. One very large and complex industrial system that has benefited from CFD-based simulations is the steel blast furnace system. The problem with the CFD-based simulation approach is that it tends to be very slow for generating data. The CFD-only approach may not be fast enough for use in real-time decisionmaking. To address this issue, in this work, the authors propose the use of machine learning techniques to train and test models based on data generated via CFD simulation. Regression models based on neural networks are compared with tree-boosting models. In particular, several areas (tuyere, raceway, and shaft) of the blast furnace are modeled using these approaches. The results of the model training and testing are presented and discussed. The obtained R 2 metrics are, in general, very high. The results appear promising and may help to improve the efficiency of operator and process engineer decisionmaking when running a blast furnace.

97 MATHEMATICS AND COMPUTING↗

Scenario Complexity for Unmanned Aircraft System Traffic

This work introduces an approach to estimate the complexity of a low-altitude air traffic scenario involving multiple UASs using mathematical programming. Given a set of multi-point UAS flight trajectories, vehicle dynamics, and a conflict resolution algorithm, an abstract model is developed such that it can be solved quickly using a mathematical programming optimization software without running high-fidelity simulations that can be computationally expensive and may not suit real-time applications. In the abstract model, each vehicle is represented by a time-varied vector associated with position, speed, and heading information. The total extra distance that aircraft need to divert from their original routes to avoid collisions is computed and used to setup a quadratic programming formula. The metrics including the number of conflicts and extra distances travelled by all vehicles are then utilized to estimate the complexity of a given UAS flight scenario. Results and verification against high-fidelity simulations will be provided in the final draft.

UTM↗

Partial Air Sparge System Abandonment at Launch Complex 39B, SWMU 009 Implementation Report

This project included AS system abandonment activities for a small portion of the LC39B AS system in support of crane operations planned at LC39B. The specific objectives are: •Remove/cap AS system components and abandon AS/monitoring wells (MWs) within identified area in support of critical mission support construction operations; •Photograph, document size, and location of any AS piping to be left in place; •Provide as-builts with survey data of piping that is left in place so it can be provided to the KSC Mater Planning office for recording by RPM; and •Properly transport concrete and other construction debris off site and dispose of at an appropriate facility in accordance with all local and federal regulations. Following completion of abandonment activities, ensure all areas of operation are graded so no trip hazards exist.

Jason J Bublitz↗

Interface learning in fluid dynamics: Statistical inference of closures within micro–macro-coupling models

Many complex multiphysics systems in fluid dynamics involve using solvers with varied levels of approximations in different regions of the computational domain to resolve multiple spatiotemporal scales present in the flow. The accuracy of the solution is governed by how the information is exchanged between these solvers at the interface and several methods have been devised for such coupling problems. In this article, we construct a data-driven model by spatially coupling a microscale lattice Boltzmann method (LBM) solver and macroscale finite difference method (FDM) solver for reaction-diffusion systems. The coupling between the micro-macro solvers has one to many mapping at the interface leading to the interface closure problem, and we propose a statistical inference method based on neural networks to learn this closure relation. The performance of the proposed framework in a bifidelity setting partitioned between the FDM and LBM domain shows its promise for complex systems where analytical relations between micro-macro solvers are not available.

42 ENGINEERING↗

Mathematical concepts for modeling human behavior in complex man-machine systems

Many human behavior (e.g., manual control) models have been found to be inadequate for describing processes in certain real complex man-machine systems. An attempt is made to find a way to overcome this problem by examining the range of applicability of existing mathematical models with respect to the hierarchy of human activities in real complex tasks. Automobile driving is chosen as a baseline scenario, and a hierarchy of human activities is derived by analyzing this task in general terms. A structural description leads to a block diagram and a time-sharing computer analogy.

Johannsen, G.↗

Record-quality GaAs two-dimensional hole systems

The complex band structure, large spin-orbit induced band splitting, and heavy effective mass of two-dimensional (2D) hole systems hosted in GaAs quantum wells render them rich platforms to study many-body physics and ballistic transport phenomena. Here we report ultra-high-quality (001) GaAs 2D hole systems, fabricated using molecular beam epitaxy and modulation doping, with mobility values as high as 5.8 × 10 6 cm 2 /(V s) at a hole density of p = 1.3 × 10 11 /cm 2 , implying a mean free path of ≃ 27 μm. In the low-temperature magnetoresistance trace of this sample, we observe high-order fractional quantum Hall states up to the Landau level filling ν = 12/25 near ν = 1/2. Furthermore, we see a deep minimum develop at ν = 1/5 in the magnetoresistance of a sample with a much lower hole density of p = 4.0 × 10 10 /cm 2 where we measure a mobility of 3.6 × 10 6 cm2/(V s). Finally, these improvements in sample quality were achieved by the reduction of residual impurities both in the GaAs channel and in the AlGaAs barrier material, as well as optimization in the design of the sample structure.

2-dimensional systems↗