SEARCH · Search NASA

Results for “Research process automation”

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 523 records · Page 29

All sources NASA NTRS DOE OSTI

NASA NTRS2020

Run Time Assurance as an Alternate Concept to Contemporary Development Assurance Processes

NASA and the FAA sought industry research to identify and evaluate alternate concepts for assuring safety of airborne systems. This report documents a research effort focused on the evaluation of Run Time Assurance (RTA) as applied to a novel, airborne system architecture. The RTA pattern is applied to a case study focused on a notional integrated flight and propulsion control system for a DEP VTOL aircraft. During flight, while the high-automation algorithms are operating, the RTA system will monitor the aircraft state for any impending violation of safety requirements. When necessary, it will switch to the low-automation software to prevent such violations. Assurance practices for both baseline industry activities and the RTA approach were captured and compared to illustrate the required engineering design considerations, and possible advantages and disadvantages of each approach as part of this case study.

Eric M. Peterson↗

DOE OSTI2024

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗

DOE OSTI2024

ELECTRONIC STRUCTURE METHODS AND PROTOCOLS WITH APPLICATION TO DYNAMICS, KINETICS AND THERMOCHEMISTRY

Hydrocarbon combustion involves the reaction dynamics of a tremendous number of species beginning with many-component fuel mixtures and proceeding via a complex system of intermediates to form primary and secondary products. Combustion conditions corresponding to new advanced engines and/or alternative fuels rely increasingly on autoignition and low-temperature-combustion chemistry. In these regimes various transient radical species such as HO2, ROO·, ·QOOH, HCO, NO2, HOCO, and Criegee intermediates play important roles in determining the detailed as well as more general dynamics. A clear understanding and accurate representation of these processes is needed for effective modeling. Given the difficulties associated with making reliable experimental measurements of these systems, computation can play an important role in developing these energy technologies. Accurate calculations have their own challenges since even within the simplest dynamical approximations such as transition state theory, the rates depend exponentially on critical barrier heights and these may be sensitive to the level of quantum chemistry. Moreover, it is well-known that in many cases it is necessary to go beyond statistical theories and consider the dynamics. Quantum tunneling, resonances, radiative transitions, and non-adiabatic effects governed by spin-orbit or derivative coupling can be determining factors in those dynamics. Building upon progress made during a period of prior support through the DOE Early Career Program, this project combines developments in the areas of potential energy surface (PES) fitting and multistate multireference quantum chemistry to allow spectroscopically and dynamically/kinetically accurate investigations of key molecular systems (such as those mentioned above), many of which are radicals with strong multireference character and have the possibility of multiple electronic states contributing to the observed dynamics. An ongoing area of investigation is to develop general strategies for robustly convergent electronic structure theory for global multichannel reactive surfaces including diabatization of energy and other relevant surfaces such as dipole transition. Combining advances in ab initio methods with automated interpolative PES fitting allows the construction of high-quality PESs (incorporating thousands of high-level data) to be done rapidly through parallel processing on high-performance computing (HPC) clusters. In addition, new methods and approaches to electronic structure theory will be developed and tested through applications. This project will explore limitations in traditional multireference calculations (e.g., MRCI) such as those imposed by internal contraction, lack of high-order correlation treatment and poor scaling. Methods such as DMRG-based extended active-space CASSCF and various Quantum Monte Carlo (QMC) methods will be applied (including VMC/DMC and FCIQMC). Insight into the relative significance of different orbital spaces and the robustness of application of these approaches on leadership class computing architectures will be gained. Synergy with other components of this research program such as automated PES fitting and multireference quantum chemistry will be used to address challenges encountered by the standard approaches to computational thermochemistry (those being single-reference quantum chemistry and perturbative treatments of the anharmonic vibrational energy, which break down for some cases of electronic structure or floppy strongly coupled vibrational modes).

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2024

Building a Simplistic Automatic Extruder: Instrument Development Opportunities for the Laboratory

This work presents an automatic extruder as a research experience for undergraduate students. The system offers a user-friendly approach to preparing vesicles, such as liposomes or polymersomes, with a defined size and polydispersity properties crucial for research in biology and macromolecules. It comprises two syringe pumps connected by a membrane filter. The setup is controlled by software. Compared to manual extrusion, this automated system provides advantages, such as precisely controlled variables. The project describes a tool to enhance undergraduate learning in science and engineering laboratories. Building an automatic extruder serves as a simplified model of a complex industrial process. It offers a clear advantage: automating a well-understood manual extrusion process. To make this project accessible, it is broken down into three manageable tasks: software development, hardware assembly, and testing procedures. This breakdown describes the software created, the hardware components used, and the testing procedures conducted for this project. All project data, including software code, testing data, and procedures, are freely available online. This allows undergraduate students to not only begin their own projects but also contribute to this educational instrument’s ongoing development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Digital Rocks Portal (Digital Porous Media): Connecting data, simulation and community

Digital Rocks Portal (DRP, https://www.digitalrocksportal.org) organizes and preserves imaged datasets and experimental measurements of porous materials in subsurface, and beyond, with the mission to connect them to simulation and analysis, as well as educate the research community. We have over 150 projects represented in more than 200 publications, and an active community that reuses the data, most recently in multiple machine learning applications for automating image analysis as well as the prediction of transport. Such automation is crucial for performing formation evaluation tasks in near-real time. We present benchmark datasets that have played a role in recent machine learning prediction successes in the field. We further discuss the vision for further research advances, educational materials, as well as growth and sustainability plan of this digital rock physics community resource. In particular, we are in the process of expanding into a broader repository of engineered porous materials, specifically those for energy storage and the portal will transition to Digital Porous Media (DPM) in near future.

58 GEOSCIENCES↗

NASA NTRS1983

A system for intelligent teleoperation research

The Automation Technology Branch of NASA Langley Research Center is developing a research capability in the field of artificial intelligence, particularly as applicable in teleoperator/robotics development for remote space operations. As a testbed for experimentation in these areas, a system concept has been developed and is being implemented. This system termed DAISIE (Distributed Artificially Intelligent System for Interacting with the Environment), interfaces the key processes of perception, reasoning, and manipulation by linking hardware sensors and manipulators to a modular artificial intelligence (AI) software system in a hierarchical control structure. Verification experiments have been performed: one experiment used a blocksworld database and planner embedded in the DAISIE system to intelligently manipulate a simple physical environment; the other experiment implemented a joint-space collision avoidance algorithm. Continued system development is planned.

Orlando, N. E.↗

NASA NTRS1992

Intelligent systems for KSC ground processing

The ground processing and launch of Shuttle vehicles and their payloads is the primary task of Kennedy Space Center. It is a process which is largely manual and contains little inherent automation. Business is conducted today much as it was during previous NASA programs such as Apollo. In light of new programs and decreasing budgets, NASA must find more cost effective ways in which to do business while retaining the quality and safety of activities. Advanced technologies including artificial intelligence could cut manpower and processing time. This paper is an overview of the research and development in Al technology at KSC with descriptions of the systems which have been implemented, as well as a few under development which are promising additions to ground processing software. Projects discussed cover many facets of ground processing activities, including computer sustaining engineering, subsystem monitor and diagnosis tools and launch team assistants. The deployed Al applications have proven an effectiveness which has helped to demonstrate the benefits of utilizing intelligent software in the ground processing task.

Heard, Astrid E.↗

NASA NTRS1990

Embedded CLIPS for SDI BM/C3 simulation and analysis

Nichols Research Corporation is developing the BM/C3 Requirements Analysis Tool (BRAT) for the U.S. Army Strategic Defense Command. BRAT uses embedded CLIPS/Ada to model the decision making processes used by the human commander of a defense system. Embedding CLlPS/Ada in BRAT allows the user to explore the role of the human in Command and Control (C2) and the use of expert systems for automated C2. BRAT models assert facts about the current state of the system, the simulated scenario, and threat information into CLIPS/Ada. A user-defined rule set describes the decision criteria for the commander. We have extended CLIPS/Ada with user-defined functions that allow the firing of a rule to invoke a system action such as weapons release or a change in strategy. The use of embedded CLIPS/Ada will provide a powerful modeling tool for our customer at minimal cost.

Gossage, Brett↗

NASA NTRS2018

Laser Ablation Surface Treatment of Structural Aerospace Composites and Metal Alloys for Adhesive Bonding

NASA Langley Research Center (LaRC) has been involved over the past decade in the development of laser ablation as a method to surface treat aerospace structural fiber reinforced composites (CFRPs) and metal alloys. [1- 18] Laser surface treatment has been shown to be a rapid, high precision, and reproducible method for surface treatment of these materials, and is amenable to automation. The laser ablation process removes surface contamination such as silicones, creates surface roughness, and chemically activates a surface for bonding. The degree of ablation is controllable by adjusting laser parameters. In the case of CFRPs, ablation can be performed without damage to any underlying carbon fibers. In the case of metal alloys, ablation is possible without surface embrittlement, heat damage or creation of undesirable grain structures or morphologies. The optimum laser treatment conditions are substrate dependent and generally are influenced by laser wavelength and pulse duration (typically fixed for a laser system), and laser power. In the case of metal alloys such as Ti-6Al-4V, the laser ablation process eliminates the need for several steps of the conventional processes, including hydrofluoric (HF) acid and caustic treatment. These steps are often conducted in dip tanks and require costly facilities and environmentally unfriendly liquids. In addition, the laser can create nano-porosity on the Ti-6Al-4V alloy surface allowing for sol-gel penetration and thereby creating a gradient interface with improved temperature and mechanical performance. NASA LaRC has also been involved with the development of in-line characterization methods compatible with the laser treatment process to rapidly determine the presence of key contaminates such as silicones that, even at very low concentrations, are a threat to adhesive bonding. A spectroscopic technique called micro-laser induced breakdown spectroscopy (u-LIBS) has been developed to rapidly detect silicones at concentrations below those known to cause bonding problems. This technique requires no sample preparation, vacuum or inert atmosphere, has no practical size limitations, and provides nearly instantaneous feedback to the operator. This presentation will give an overview and update of these developments with specific examples highlighted.

Connell, John W.↗

NASA NTRSDate not supplied

Managing the Digital Thread for Structural Applications With Fit for Purpose Materials

With the increased emphasis on reducing the cost and time to market of new materials, the need for analytical tools that enable the virtual design and optimization of materials throughout their processing - internal structure - property - performance envelope, along with the capturing and storing of the associated material and model information across its lifecycle, has become critical. This need is also fueled by the demands for higher efficiency in material testing; consistency, quality and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. Consequently, at NASA Glenn Research Center a robust information management system that manages the digital thread across the full material life (i.e., capture, analysis, maintenance, and dissemination of data) cycle directed at the design of ‘fit-for-purpose materials’ is under development. To this end the Application Table has been incorporated within NASA Glenn Research Center’s ICME Information Management framework within the ANSYS Granta MI tool. The Application Table provides a place where material and structural application information/requirements can be linked to marry the “design-the-material” (structural engineering) and the “design-with-material” (material science) paradigms and thereby enable application-driven design and optimization of materials and structures. In additional several associated toolsets, specifically: AIMAOS (Automated Information Management Across Organizations and Scales), Py MILab, and JARIMIS (Just A Rather Intelligent Material Interrogation System) are also under development to assist in the judicious automation of this process. AIMOAS offers users an interactive graphical user interface for connecting material information management systems with both commercial and in-house simulation tools at various length scales to enable such automation in the handoff across scales and maintenance of material digital twins and the digital thread. Py MILab, is an automatic framework for the capture, analysis, maintenance, and storage of material test data. Py MILab uses a modular approach for capturing raw data, analyzing the data, and storing the data in a database, interfaced by neutral file structures, to promote plug-and-play capabilities for various analysis types. Finally, JARIMIS is an expert system that integrates various materials informatics tools (e.g., MicroNet, Surrogate ML models, ANSYS Granta MI, etc.) to enable inverse design of materials and facilitate the application of machine learning (ML) and data science with human in the loop decision making to rapidly discover and optimize new materials.

Digital Transformation↗

DOE OSTI2023

Large Language Models (LLMs) for Energy Systems Research

The integration of Large Language Models (LLMs) in energy systems research promises transformative results, as demonstrated in this work, particularly in the realms of information retrieval and legal document analysis. We have developed a chat-based interface, specifically designed to query an extensive corpus of technical reports from the National Renewable Energy Laboratory (NREL). This interface capitalizes on the natural language processing capabilities of LLMs, providing future consumers of NREL research with a user-friendly platform to access and extract valuable information from technical documents, thus enhancing the dissemination of research to the public. In addition to information retrieval, we have employed LLMs to extract renewable energy siting ordinances from a variety of legal documents, a task traditionally driven by significant human labor. This automated extraction not only supports the ongoing development of the high-impact NREL siting ordinance database but also ensures the database's accuracy and comprehensiveness. Crucially, we have augmented the performance of LLMs through the integration of a decision tree framework, resulting in a substantial improvement in extraction accuracy. Comparative analysis with manual efforts has shown that this approach not only rivals but also significantly surpasses human accuracy, heralding increased reliability in legal document analysis for energy systems research. To democratize access to these advancements and foster collaborative research, we introduce the "Energy Language Model" (ELM), an open-source software package. ELM encapsulates the methodologies and tools developed in this work, providing researchers and practitioners with a robust toolkit to conduct similar analyses within their respective domains. Through these contributions, this work underscores the immense potential of LLMs in revolutionizing energy systems research, improving accuracy, efficiency, and accessibility in the field.

automation↗

DOE OSTI2024

SUBTASK 1.6 – BASIN ELECTRIC CARBON STORAGE RESEARCH PROJECT: NOVEL MONITORING TECHNIQUES

The Energy & Environmental Research Center (EERC) conducted baseline activities associated with an applied research project at Basin Electric Power Cooperative’s (Basin’s) carbon capture and storage (CCS) site in Beulah, North Dakota, to establish novel carbon storage-monitoring techniques as commercial methods under Cooperative Agreement No. DE-FE0024233, Subtask 1.6. The following report summarizes the baseline activities performed and briefly describes the subsequent (operational monitoring) activities that have been proposed to the U.S. Department of Energy (DOE) as part of the overall project to develop and demonstrate novel monitoring techniques at North America’s largest permitted CCS operation. Dakota Gasification Company (DGC), a wholly owned subsidiary of Basin, owns and operates the Great Plains Synfuels Plant (GPSP) approximately 5 miles northwest of the town of Beulah, North Dakota (Figure 1). In 2023, DGC received approval from the North Dakota Industrial Commission (NDIC) to develop a storage facility on-site for injecting a stream of carbon dioxide (CO2) captured from GPSP. DGC will transport the captured CO2 stream with approximately 6.8 miles of transmission lines that extend north of GPSP and inject >1 million tonnes (MMt) of CO2 annually (>1 MMt/yr) over a 12-year period with up to six underground injection control (UIC) Class VI-compliant injection wells completed in the Broom Creek Formation, a predominantly sandstone reservoir and saline aquifer underlying GPSP. The Broom Creek Formation lies approximately 5900 feet (ft) below ground surface (bgs) at GPSP. The commercial scale (i.e., >1 MMt/yr) of DGC’s permitted carbon storage project is ideal for developing and testing the novel monitoring techniques included within Subtask 1.6. The goals of this project are to demonstrate 1) the cost-effectiveness of novel monitoring technologies included as part of this research, 2) technology capability for tracking the CO2 plume and/or associated pressure response in the subsurface and monitoring out-of-zone migration, and 3) compliance with UIC Class VI program requirements. The research activities proposed for the overall project include 1) design of an automated, integrated, modular (AIM) monitoring station; 2) time-lapse electromagnetic (EM) field surveys; 3) drone-based surveillance studies; 4) time-lapse monitoring with seismic methods; 5) advanced wellbore-monitoring methods; 6) deployment of an AIM monitoring network; 7) EM monitoring of CO2 with real-time data processing; 8) continued seasonal drone-based surveillance studies; 9) seismic monitoring with passive and active surveys; and 10) wellbore monitoring with nuclear magnetic resonance (NMR) for near-surface characterization. Completion of Activities 1.0–5.0 (baseline activities) are described in this report. Upon authorization of funding by DOE, the EERC will initiate Activities 6.0– 10.0 (operational monitoring activities). Current state-of-the-art (SOA) carbon storage-monitoring techniques require countless labor hours dedicated to the acquisition of data. Once data are gathered, these SOA techniques often rely on commercial facilities to process raw data from the field. However, it is anticipated that next-generation monitoring techniques, such as those being demonstrated, will lower acquisition footprints, be less operationally intensive, and improve data acquisition efficiencies. These new techniques are more conducive to the application of machine learning, artificial intelligence, and automation, thus providing a pathway for integration into active control systems, informing site operability, and improving the integration of data for future CCS projects across the United States. Additionally, reclaimed and active mining lands are present within the project site, creating a unique opportunity to demonstrate the effectiveness of remote sensing and surface-based geophysics monitoring techniques at similar project sites that may include disturbed, unconsolidated, or actively excavated near-surface environments. The efforts included in the overall project will produce necessary designs, learnings, and data acquired during the baseline and operational monitoring periods that are necessary for time-lapse demonstration and validation of the described monitoring techniques. In addition, it is anticipated that the monitoring technologies included in this study will be compliant with UIC Class VI requirements to enable the potential for implementation at other CCS sites across the United States.

42 ENGINEERING↗

NASA NTRS2012

Mass Analyzers Facilitate Research on Addiction

The famous go/no go command for Space Shuttle launches comes from a place called the Firing Room. Located at Kennedy Space Center in the Launch Control Center (LCC), there are actually four Firing Rooms that take up most of the third floor of the LCC. These rooms comprise the nerve center for Space Shuttle launch and processing. Test engineers in the Firing Rooms operate the Launch Processing System (LPS), which is a highly automated, computer-controlled system for assembly, checkout, and launch of the Space Shuttle. LPS monitors thousands of measurements on the Space Shuttle and its ground support equipment, compares them to predefined tolerance levels, and then displays values that are out of tolerance. Firing Room operators view the data and send commands about everything from propellant levels inside the external tank to temperatures inside the crew compartment. In many cases, LPS will automatically react to abnormal conditions and perform related functions without test engineer intervention; however, firing room engineers continue to look at each and every happening to ensure a safe launch. Some of the systems monitored during launch operations include electrical, cooling, communications, and computers. One of the thousands of measurements derived from these systems is the amount of hydrogen and oxygen inside the shuttle during launch.

Source record↗

DOE OSTI2025

Automated tabletop exfoliation and identification of monolayer graphene flakes

Over the past two decades, graphene has been intensively studied because of its remarkable mechanical, optical, and electronic properties. Initial studies were enabled by manual “Scotch Tape” exfoliation; nearly two decades later, this method is still widely used to obtain chemically pristine flakes of graphene and other 2D van der Waals materials. Unfortunately, the yield of large, pristine flakes with uniform thickness is inconsistent. Thus, significant time and effort are required to exfoliate and locate flakes suitable for fabricating multilayer van der Waals heterostructures. Here, we describe a relatively affordable tabletop device (the “eXfoliator”) that can reproducibly control key parameters and largely automate the exfoliation process. In a typical exfoliation run, the eXfoliator produces 3 or more large (≥ 400 μm 2 ) high-quality graphene monolayer flakes, allowing new users to produce such flakes at a rate comparable to manual exfoliation by an experienced user. Furthermore, we use an automated mapping system and a computer vision algorithm to locate candidate flakes. Our results provide a starting point for future research efforts to identify more precisely which parameters matter for the success of exfoliation and to optimize them.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

BAMBAM (The Behavior and Advanced Mobility Big Access Model) [SWR-25-123]

Access modeling toolkit for Rust built on the RouteE Compass energy-aware route planner. The Behavior and Advanced Mobility Big Access Model (BAMBAM) is a mobility research platform for scalable access modeling. The process begins with a grid defined at some spatial granularity (e.g., census block or 1 km grid) and a variety of travel configurations. For each grid cell and configuration, the platform executes constrained searches, uses the results to index points of interest (POI), and aggregates the findings to the grid level. It provides researchers access through R or Python running on HPC. The platform automates the import and merging of datasets from a variety of sources including data.gov (with automatic merging of Tiger/Lines geometries), OpenStreetMaps, OvertureMaps, and GTFS. It is built upon RouteE Compass, a scalable, energy-aware route planner written in Rust, extended to model multiple travel modes.

Fitzgerald, Robert [National Renewable Energy Labo↗

NASA NTRS1994

Automation of reverse engineering process in aircraft modeling and related optimization problems

During the year of 1994, the engineering problems in aircraft modeling were studied. The initial concern was to obtain a surface model with desirable geometric characteristics. Much of the effort during the first half of the year was to find an efficient way of solving a computationally difficult optimization model. Since the smoothing technique in the proposal 'Surface Modeling and Optimization Studies of Aerodynamic Configurations' requires solutions of a sequence of large-scale quadratic programming problems, it is important to design algorithms that can solve each quadratic program in a few interactions. This research led to three papers by Dr. W. Li, which were submitted to SIAM Journal on Optimization and Mathematical Programming. Two of these papers have been accepted for publication. Even though significant progress has been made during this phase of research and computation times was reduced from 30 min. to 2 min. for a sample problem, it was not good enough for on-line processing of digitized data points. After discussion with Dr. Robert E. Smith Jr., it was decided not to enforce shape constraints in order in order to simplify the model. As a consequence, P. Dierckx's nonparametric spline fitting approach was adopted, where one has only one control parameter for the fitting process - the error tolerance. At the same time the surface modeling software developed by Imageware was tested. Research indicated a substantially improved fitting of digitalized data points can be achieved if a proper parameterization of the spline surface is chosen. A winning strategy is to incorporate Dierckx's surface fitting with a natural parameterization for aircraft parts. The report consists of 4 chapters. Chapter 1 provides an overview of reverse engineering related to aircraft modeling and some preliminary findings of the effort in the second half of the year. Chapters 2-4 are the research results by Dr. W. Li on penalty functions and conjugate gradient methods for quadratic programming problems.

Li, W.↗

NASA NTRS2000

A Conceptual Design of a Departure Planner Decision Aid

Terminal area Air Traffic Management handles both arriving and departing traffic. To date, research work on terminal area operations has focused primarily on the arrival flow and typically departures are taken into account only in an approximate manner. However, arrivals and departures are highly coupled processes especially in the terminal airspace, with complex interactions and sharing of the same airport resources between arrivals and departures taking place in practically every important terminal area. Therefore, the addition of automation aids for departures, possibly in co-operation with existing arrival flow automation systems, could have a profound contribution in enhancing the overall efficiency of airport operations. This paper presents the conceptual system architecture for such an automation aid, the Departure Planner (DP). This architecture can be used as a core in the development of decision-aiding systems to assist air traffic controllers in improving the performance of departure operations and optimize runway time allocation among different operations at major congested airports. The design of such systems is expected to increase the overall efficiency of terminal area operations and yield benefits for all stakeholders involved in Air Traffic Management (ATM) operations, users as well as service providers.

Anagnostakis, Ioannis↗

NASA NTRS2014

Q-Thruster Breadboard Campaign Project

Dr. Harold "Sonny" White has developed the physics theory basis for utilizing the quantum vacuum to produce thrust. The engineering implementation of the theory is known as Q-thrusters. During FY13, three test campaigns were conducted that conclusively demonstrated tangible evidence of Q-thruster physics with measurable thrust bringing the TRL up from TRL 2 to early TRL 3. This project will continue with the development of the technology to a breadboard level by leveraging the most recent NASA/industry test hardware. This project will replace the manual tuning process used in the 2013 test campaign with an automated Radio Frequency (RF) Phase Lock Loop system (precursor to flight-like implementation), and will redesign the signal ports to minimize RF leakage (improves efficiency). This project will build on the 2013 test campaign using the above improvements on the test implementation to get ready for subsequent Independent Verification and Validation testing at Glenn Research Center (GRC) and Jet Propulsion Laboratory (JPL) in FY 2015. Q-thruster technology has a much higher thrust to power than current forms of electric propulsion (~7x Hall thrusters), and can significantly reduce the total power required for either Solar Electric Propulsion (SEP) or Nuclear Electric Propulsion (NEP). Also, due to the high thrust and high specific impulse, Q-thruster technology will greatly relax the specific mass requirements for in-space nuclear reactor systems. Q-thrusters can reduce transit times for a power-constrained architecture.

White, Harold↗