SEARCH · Engineering Papers

Results for “network operational objectives”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 451 records · Page 25

All sources NASA NTRS DOE OSTI

NASA NTRS1989

Ames life science telescience testbed evaluation

Eight surrogate spaceflight mission specialists participated in a real-time evaluation of remote coaching using the Ames Life Science Telescience Testbed facility. This facility consisted of three remotely located nodes: (1) a prototype Space Station glovebox; (2) a ground control station; and (3) a principal investigator's (PI) work area. The major objective of this project was to evaluate the effectiveness of telescience techniques and hardware to support three realistic remote coaching science procedures: plant seed germinator charging, plant sample acquisition and preservation, and remote plant observation with ground coaching. Each scenario was performed by a subject acting as flight mission specialist, interacting with a payload operations manager and a principal investigator expert. All three groups were physically isolated from each other yet linked by duplex audio and color video communication channels and networked computer workstations. Workload ratings were made by the flight and ground crewpersons immediately after completing their assigned tasks. Time to complete each scientific procedural step was recorded automatically. Two expert observers also made performance ratings and various error assessments. The results are presented and discussed.

Haines, Richard F.↗

NASA NTRS2014

America's Next Great Ship: Space Launch System Core Stage Transitioning from Design to Manufacturing

The Space Launch System (SLS) Program is essential to achieving the Nation's and NASA's goal of human exploration and scientific investigation of the solar system. As a multi-element program with emphasis on safety, affordability, and sustainability, SLS is becoming America's next great ship of exploration. The SLS Core Stage includes avionics, main propulsion system, pressure vessels, thrust vector control, and structures. Boeing manufactures and assembles the SLS core stage at the Michoud Assembly Facility (MAF) in New Orleans, LA, a historical production center for Saturn V and Space Shuttle programs. As the transition from design to manufacturing progresses, the importance of a well-executed manufacturing, assembly, and operation (MA&O) plan is crucial to meeting performance objectives. Boeing employs classic techniques such as critical path analysis and facility requirements definition as well as innovative approaches such as Constraint Based Scheduling (CBS) and Cirtical Chain Project Management (CCPM) theory to provide a comprehensive suite of project management tools to manage the health of the baseline plan on both a macro (overall project) and micro level (factory areas). These tools coordinate data from multiple business systems and provide a robust network to support Material & Capacity Requirements Planning (MRP/CRP) and priorities. Coupled with these tools and a highly skilled workforce, Boeing is orchestrating the parallel buildup of five major sub assemblies throughout the factory. Boeing and NASA are transforming MAF to host state of the art processes, equipment and tooling, the most prominent of which is the Vertical Assembly Center (VAC), the largest weld tool in the world. In concert, a global supply chain is delivering a range of structural elements and component parts necessary to enable an on-time delivery of the integrated Core Stage. SLS is on plan to launch humanity into the next phase of space exploration.

Birkenstock, Benjamin↗

DOE OSTI2025

Toward Drilling the Perfect Geothermal Well: An International Research Coordination Network for Geothermal Drilling Optimization Supported by Deep Machine Learning and Cloud Based Data Aggregation

The EDGE project, supported by the U.S. Department of Energy Geothermal Technologies Office under award DE-EE0008793, established a data-driven framework for improving the efficiency, cost-effectiveness, and reliability of geothermal well drilling. The project focused on developing scalable data infrastructure, advanced machine learning and probabilistic models, and integrated analytics tools to support continuous drilling optimization. A central objective was to reduce geothermal drilling costs by up to seventy percent while minimizing the risk of well failure through predictive diagnostics and adaptive planning. Over the project period, a comprehensive data repository was designed and deployed, incorporating records from over one hundred geothermal wells across varied geological settings. This repository supported both structured and unstructured data and adhered to FAIR data principles, enabling provenance tracking, quality control, and standardized metadata. The project introduced automated ingestion pipelines and a cloud-hosted platform that facilitated access to raw, processed, and derived datasets. This infrastructure served as the foundation for model development and analysis. Machine learning workflows were developed to predict key drilling metrics including rate of penetration, non-productive time, and total drilling costs. Self-organizing maps and dimensionality reduction methods were used to uncover operational patterns and outliers, while supervised learning algorithms such as random forests and deep neural networks were applied to forecast performance outcomes. The models were validated on heterogeneous datasets from both U.S. and Icelandic fields, demonstrating variable but significant predictive accuracy. The results indicated that finer temporal resolution, inclusion of lithological data, and consistency in operational annotations could substantially improve model performance. The project also implemented process mining techniques to reconstruct state-transition models from drilling event logs. These models enabled the identification of deviations from optimal workflows and provided insights into recurring failure modes. Analysis of non-productive time highlighted the impact of equipment failures, geological challenges, and human factors, offering opportunities for targeted mitigation strategies. The EDGE Dashboard was developed as a web-based expert system integrating data visualization, model outputs, and user-driven queries. It provided an accessible interface for operators to explore historical data, evaluate predicted outcomes, and compare drilling scenarios. Initial feedback from project partners suggested that the dashboard could serve as a foundation for more advanced advisory and optimization tools. Overall, the EDGE project demonstrated the feasibility and value of applying modern data science techniques to geothermal drilling. It delivered a set of interoperable tools and models that can support more efficient, lower-risk well development. The findings point toward a viable path for transitioning from advisory analytics to semi-autonomous drilling systems, contingent on continued collaboration, expanded datasets, and field validation. The project results have immediate relevance for drilling operations, data management practices, and future geothermal R&D efforts aimed at achieving reliable, cost-competitive geothermal energy at scale.

15 GEOTHERMAL ENERGY↗

NASA NTRS1999

1997 NASA/MSFC Summer Teacher Enrichment Program

This is a report on the follow-up activities conducted for the 1997 NASA Summer Teacher Enrichment Program (STEP), which was held at the George C. Marshall Space Flight Center (MSFC) for the seventh consecutive year. The program was conducted as a six-week session with 17 sixth through twelfth grade math and science teachers from a six-state region (Alabama, Arkansas, Iowa, Louisiana, Mississippi and Missouri). The program began on June 8, 1997, and ended on July 25, 1997. The long-term objectives of the program are to: increase the nation's scientific and technical talent pool with a special emphasis on underrepresented groups, improve the quality of pre-college math and science education, improve math and science literacy, and improve NASA's and pre-college education's understandings of each other's operating environments and needs. Short-term measurable objectives for the MSFC STEP are to: improve the teachers' content and pedagogy knowledge in science and/or mathematics, integrate applications from the teachers' STEP laboratory experiences into science and math curricula, increase the teachers' use of instructional technology, enhance the teachers' leadership skills by requiring them to present workshops and/or inservice programs for other teachers, require the support of the participating teacher(s) by the local school administration through a written commitment, and create networks and partnerships within the education community, both pre-college and college. The follow-up activities for the 1997 STEP included the following: academic-year questionnaire, site visits, academic-year workshop, verification of commitment of support, and additional NASA support.

Source record↗

NASA NTRSDate not supplied

Scheduling Position, Navigation and Time Service Requests from Non-dedicated Lunar Constellations

This paper presents a centralized scheduler that satisfies user requests for Position, Navigation, and Time (PNT) services from an ad-hoc, non-dedicated orbital constellation around the Moon. Traditional, dedicated GNSS networks provide service 24/7, which allows users to acquire localization services at-will. For ad-hoc networks, a coordinated schedule is needed to ensure Quality of Service (QoS) guarantees for user localization, while satisfying non-dedicated assets’ usage constraints. This scheduler bridges this coordination gap by leveraging Mixed Integer-Linear Programming (MILP) to schedule this “as-needed” localization service while respecting the constraints on each asset. In upcoming decades there is expected to be a substantial increase in Lunar missions. Many of these missions will feature low-cost surface assets near the moon’s polar regions and small-sat science missions in orbit. Most missions need PNT capabilities to ensure safe operations and meet their science objectives, but low-cost missions may not be able to support the large power, mass, and weight that a weak GNSS or DSN based navigation solution would entail. Asset localization has been demonstrated using a decentralized extended Kalman Filter (DEKF) in the previously presented Lunar Autonomous PNT System (LAPS). Within the LAPS simulation environment, a module has been developed to generate the coordinated user-asset schedules described above; this Service Scheduler Module (SSM) allows for complete end-to-end testing of the entire system. Within SSM, a user service request consists of a location on the Lunar surface, a cumulative service duration, and a window in which service must occur. SSM takes as input these requests and the LAPS-predicted positional degree of precision as the QoS for each available set of orbital assets. A simple, baseline MILP model is formulated to provide the highest-precision service balanced across all requests. To reflect the non-dedicated nature of the constellation, this baseline model is augmented with additional asset-specific load capacity constraints or availability constraints. The load capacity constraints limit total time spent providing service, and the availability constraints reflect blockout times or availability windows when the assets are not otherwise occupied. SSM outputs two schedules: the user schedule to indicate their service times and expected QoS, and a satellite schedule to be transmitted to the orbiting constellation, describing when each non-dedicated asset provides PNT service. SSM is predominantly implemented in MATLAB and allows the use of any MILP solver to generate the resulting schedules. This paper describes the SSM - LAPS interface, how the output of LAPS is used to construct the MILP, and how SSM provides user localization service while satisfying constraints. It will also demonstrate the tool’s flexibility for formulating schedules for the end user and the constellation, focusing on scenarios that match real-world proposed missions. It will detail how SSM can be used to compare the addition of load capacity constraints, satellite availability constraints, and QoS guarantees for the users. Finally, we describe how SSM can be used to support the design of the ad-hoc constellation itself. The resulting integrated capability will support the design of future ad-hoc Lunar PNT networks, enabling high-quality, low-cost Lunar exploration

Swarm↗

NASA NTRS2000

Intelligence Applied to Air Vehicles

The exponential growth in information technology has provided the potential for air vehicle capabilities that were previously unavailable to mission and vehicle designers. The increasing capabilities of computer hardware and software, including new developments such as neural networks, provide a new balance of work between humans and machines. This paper will describe several NASA projects, and review results and conclusions from ground and flight investigations where vehicle intelligence was developed and applied to aeronautical and space systems. In the first example, flight results from a neural network flight control demonstration will be reviewed. Using, a highly-modified F-15 aircraft, a NASA/Dryden experimental flight test program has demonstrated how the neural network software can correctly identify and respond to changes in aircraft stability and control characteristics. Using its on-line learning capability, the neural net software would identify that something in the vehicle has changed, then reconfigure the flight control computer system to adapt to those changes. The results of the Remote Agent software project will be presented. This capability will reduce the cost of future spacecraft operations as computers become "thinking" partners along with humans. In addition, the paper will describe the objectives and plans for the autonomous airplane program and the autonomous rotorcraft project. Technologies will also be developed.

Rosen, Robert↗

NASA NTRS2008

Performance of a Local Mesoscale Model with Data Denial

Forecasters at the 45th Weather Squadron (45 WS) use observations from the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) wind tower network and daily rawinsonde observations (RAOB) to issue and verify wind advisories, watches, and warnings for operations. They are also used by the Spaceflight Meteorology Group and Melbourne, Florida National Weather Service to initialize locally run mesoscale models. Due to impending budget cuts, some or all of the mainland wind towers and RAOBs may be eliminated, The loss of these data may significantly impact the forecast capability of the 45 WS and SMG. The Applied Meteorology Unit (AMU) was tasked to conduct an objective independent modeling study to determine how important these observations are to the accuracy of the model output used by the forecasters as input to their forecasts. To accomplish this, the AMU performed a sensitivity study using the Weather Research and Forecasting (WRF) model run with and without KSC/CCAFS wind tower and CCAFS RAOB observations and assessed the accuracy of model forecasts by comparing them to the observations.

Watson, Leela↗

DOE OSTI2025

Engineering Out Industry 4.0 Cyber Risk Presentation for EnCyCriS

The increasing complexity and business requirements of operational technology (OT) devices is beginning to break the normal segmentation between information technology (IT) and OT networks. The introduction of industry 4.0 devices such as industrial internet of things (IIoT) and other intelligent industrial devices (IID), virtualized OT systems, OT cloud integration, and artificial intelligence (AI)-driven industrial control systems (ICS) has challenged traditional IT/OT cybersecurity strategies. Industry 4.0 devices are analyzed through the lens of well-regarded models such as the PERA model and confidentiality, integrity, and availability (CIA) security objectives, showing the division between what is needed and traditional cybersecurity countermeasures. In this paper, the practice of Cyber-Informed Engineering (CIE) is proposed to bridge the gap between IT/OT security, enhance the practice of cybersecurity in this modern age, and reduce the impacts of consequential events in OT.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

Engineering Out Industry 4.0 Cyber Risk

42 - ENGINEERING↗

NASA NTRS1989

Use of 3D vision for fine robot motion

An integration of 3-D vision systems with robot manipulators will allow robots to operate in a poorly structured environment by visually locating targets and obstacles. However, by using computer vision for objects acquisition makes the problem of overall system calibration even more difficult. Indeed, in a CAD based manipulation a control architecture has to find an accurate mapping between the 3-D Euclidean work space and a robot configuration space (joint angles). If a stereo vision is involved, then one needs to map a pair of 2-D video images directly into the robot configuration space. Neural Network approach aside, a common solution to this problem is to calibrate vision and manipulator independently, and then tie them via common mapping into the task space. In other words, both vision and robot refer to some common Absolute Euclidean Coordinate Frame via their individual mappings. This approach has two major difficulties. First a vision system has to be calibrated over the total work space. And second, the absolute frame, which is usually quite arbitrary, has to be the same with a high degree of precision for both robot and vision subsystem calibrations. The use of computer vision to allow robust fine motion manipulation in a poorly structured world which is currently in progress is described along with the preliminary results and encountered problems.

Lokshin, Anatole↗

NASA NTRS2005

NASA Tech Briefs, May 2005

Topics covered include: Fastener Starter; Multifunctional Deployment Hinges Rigidified by Ultraviolet; Temperature-Controlled Clamping and Releasing Mechanism; Long-Range Emergency Preemption of Traffic Lights; High-Efficiency Microwave Power Amplifier; Improvements of ModalMax High-Fidelity Piezoelectric Audio Device; Alumina or Semiconductor Ribbon Waveguides at 30 to 1,000 GHz; HEMT Frequency Doubler with Output at 300 GHz; Single-Chip FPGA Azimuth Pre-Filter for SAR; Autonomous Navigation by a Mobile Robot; Software Would Largely Automate Design of Kalman Filter; Predicting Flows of Rarefied Gases; Centralized Planning for Multiple Exploratory Robots; Electronic Router; Piezo-Operated Shutter Mechanism Moves 1.5 cm; Two SMA-Actuated Miniature Mechanisms; Vortobots; Ultrasonic/Sonic Jackhammer; Removing Pathogens Using Nano-Ceramic-Fiber Filters; Satellite-Derived Management Zones; Digital Equivalent Data System for XRF Labeling of Objects; Identifying Objects via Encased X-Ray-Fluorescent Materials - the Bar Code Inside; Vacuum Attachment for XRF Scanner; Simultaneous Conoscopic Holography and Raman Spectroscopy; Adding GaAs Monolayers to InAs Quantum-Dot Lasers on (001) InP; Vibrating Optical Fibers to Make Laser Speckle Disappear; Adaptive Filtering Using Recurrent Neural Networks; and Applying Standard Interfaces to a Process-Control Language.

Source record↗

DOE OSTI2024

Scalable Control Co-design for Resilient-by-Design Cyber Physical Systems

Critical infrastructure networks, such as power and transportation networks, are often modelled as cyber-physical systems. With ever increasing complexity of these systems, there is a need for newer and more relevant metrics and design tools that will co-optimize the physical system components and control policies to guarantee resilience against cyber and natural threats. To this end, a simulation-based control co-design computational framework that will concurrently determine the system and control parameters of a cyber-physical system to meet pre-specified resilience, operational and economic objectives has been developed. The capabilities of the developed co-design engine are demonstrated by designing the physical components and control parameters of a microgrid system that will meet its resiliency objectives when subjected to various cyber and physical threats.

42 ENGINEERING↗

NASA NTRS1984

Effects of CW interference on the carrier tracking loop of the deep space network

A radio-frequency interference (RFI) environment can cause serious problems for communications systems, such as the Deep Space Network (DSN). For this reason, it is necessary to determine first the RFI susceptibility characteristics for DSN receiving systgms. The present investigation is concerned with CW RFI's which are close in frequency to the carrier frequency. The carrier tracking loop is highly sensitive, and this type of RFI will degrade the carrier loop performance before saturation effects become noticeable. The investigation has the objective to develop an analytical model which will make it possible to predict the tracking performance of the Block IV receiver when operated in the presence of a CW RFI in the receiver passband. The Block IV receiver represents one of the DSN receivers. Attention is given to the effects of a CW RFI on a phase-locked loop, the effects of a bandpass limiter, numerical results, experimental verification, and aspects of computer simulation.

Sue, M. K.↗

NASA NTRS1989

Connectionist model-based stereo vision for telerobotics

Autonomous stereo vision for range measurement could greatly enhance the performance of telerobotic systems. Stereo vision could be a key component for autonomous object recognition and localization, thus enabling the system to perform low-level tasks, and allowing a human operator to perform a supervisory role. The central difficulty in stereo vision is the ambiguity in matching corresponding points in the left and right images. However, if one has a priori knowledge of the characteristics of the objects in the scene, as is often the case in telerobotics, a model-based approach can be taken. Researchers describe how matching ambiguities can be resolved by ensuring that the resulting three-dimensional points are consistent with surface models of the expected objects. A four-layer neural network hierarchy is used in which surface models of increasing complexity are represented in successive layers. These models are represented using a connectionist scheme called parameter networks, in which a parametrized object (for example, a planar patch p=f(h,m sub x, m sub y) is represented by a collection of processing units, each of which corresponds to a distinct combination of parameter values. The activity level of each unit in the parameter network can be thought of as representing the confidence with which the hypothesis represented by that unit is believed. Weights in the network are set so as to implement gradient descent in an energy function.

Hoff, William↗

NASA NTRS1991

Overview of the Telescience Testbed Program

The NASA's Telescience Testbed Program (TTP) conducted by the Ames Research Center is described with particular attention to the objectives, the approach used to achieve these objectives, and the expected benefits of the program. The goal of the TTP is to gain operational experience for the Space Station Freedom and the Earth Observing System programs, using ground testbeds, and to define the information and communication systems requirements for the development and operation of these programs. The results of TTP are expected to include the requirements for the remote coaching, command and control, monitoring and maintenance, payload design, and operations management. In addition, requirements for technologies such as workstations, software, video, automation, data management, and networking will be defined.

Rasmussen, Daryl N.↗

NASA NTRS2000

VLBI in the Deep Space Network: Challenges and Prospects

The purpose of this paper is to highlight the current status and prospects for VLBI in the NASA Deep Space Network (DSN). Although the prime purpose of the DSN is to support spacecraft operations and space research in deep space, this unique facility is also used on a noninterference basis with flight projects to support ground-based science experiments. The DSN VLBI capabilities are an integral part of a number of space- and ground-based projects. They include support of experiments at major radio astronomy VLBI networks (e.g., VLBA, EVN, APT), space VLBI co-observing, as well as VLBI geodesy and astrometry programs. The paper will describe for the potential DSN VLBI users 1) DSN VLBI objectives, 2) the current organizational structure and 3) current and projected capabilities.

Altunin, Valery I.↗

NASA NTRSDate not supplied

Lunar Communications and Navigation: Lunar Communications, Position, Navigation, and Time (CPNT) Architecture

The NASA Moon-to-Mars (M2M) Architecture will enable the return of humans to the Moon, establish a long-term presence there, and open more of the lunar surface to exploration than ever before. This growth of lunar activity requires robust and resilient communications, position, navigation, and time capabilities for crew safety, the command and control of spacecraft, the return of science data, and the precise telerobotic maneuvering of assets both in space and on the lunar surface. Within the M2M Architecture, the sub-architecture for Communications, Position, Navigation, and Time (CPNT) details the specific CPNT systems and infrastructure required to meet the M2M objectives. Two objectives most fundamental to the CPNT sub-architecture are: (1) develop a lunar surface, orbital, and Moon-to-Earth communications architecture that scales to support long term science, exploration, and industrial needs and (2) develop a lunar position, navigation, and timing (PNT) architecture that also scales to support long term needs. The subject presentation provides an overview of the M2M Architecture, planned mission activities, and infrastructure development underway by NASA. The presentation provides overview of the surface wireless network and the challenges associated with operating on the lunar surface.

architecture↗

DOE OSTI2023

A Computational Framework for Control Co-Design of Resilient Cyber–Physical Systems With Applications to Microgrids

Critical infrastructure networks, such as power and transportation networks, can be modelled as cyber-physical systems. As the complexity of such systems grow, there is need for developing metrics and design tools that will co-optimize the physical components of the system and the control policies to guarantee resilience against cyber and natural threats. To that end, we develop a simulation-based control co-design computational framework that will concurrently determine the system and control parameters of a cyber-physical system to meet pre-specified resilience, operational and economic objectives. Here, the capabilities of the developed co-design engine is demonstrated by designing the physical components and control parameters of a microgrid system that will meet its resiliency objectives when subjected to various cyber and physical threats.

97 MATHEMATICS AND COMPUTING↗