Engineering topics

Figueroa, Jorge

Publications and source records attributed to Figueroa, Jorge.

7 records

DOE OSTI2022

The 5 Cs of Agrivoltaic Success Factors in the United States: Lessons from the InSPIRE Research Study

The concept of agrivoltaics (combining agriculture and solar photovoltaics technologies on the same land in novel configurations) has emerged as an approach to mitigate conflicts between solar and agricultural activities by providing mutual benefits and added values to each sector. The U.S. Department of Energy has supported agrivoltaics research since 2015 through its Innovative Solar Practices Integrated with Rural Economies and Ecosystems (InSPIRE) research project (National Renewable Energy Laboratory 2022). The InSPIRE project is the most comprehensive coordinated research effort on agrivoltaics in the United States and has examined opportunities and tradeoffs at over 25 sites across the country that span crop production, pollinator habitat, ecosystem services, animal husbandry, and d. Integrating research sites with active commercial agricultural operations can introduce unique challenges for conducting research. This synthesis aims to highlight the technical and non-technical insights from InSPIRE agrivoltaic field research sites from 2015-2021 to support i) appropriate deployment of agrivoltaic projects; ii) more successful research on agrivoltaics; and iii) more effective partnerships on agrivoltaic projects. The synthesized lessons discussed here are focused less on specific case study outcomes (i.e., the percent change in crop yield in an agrivoltaics configuration), and instead more on the elements that enable and facilitate agrivoltaics projects to be installed and operated along with research to be conducted at those sites. We find that there are some insights that are applicable across all types of agrivoltaic projects, while ecosystem service projects and crop production agrivoltaic projects can often have other unique considerations.

14 SOLAR ENERGY↗

NASA NTRS2009

Smart and Intelligent Sensors

John C. Stennis Space Center (SSC) provides rocket engine propulsion testing for NASA's space programs. Since the development of the Space Shuttle, every Space Shuttle Main Engine (SSME) has undergone acceptance testing at SSC before going to Kennedy Space Center (KSC) for integration into the Space Shuttle. The SSME is a large cryogenic rocket engine that uses Liquid Hydrogen (LH2) as the fuel. As NASA moves to the new ARES V launch system, the main engines on the new vehicle, as well as the upper stage engine, are currently base lined to be cryogenic rocket engines that will also use LH2. The main rocket engines for the ARES V will be larger than the SSME, while the upper stage engine will be approximately half that size. As a result, significant quantities of hydrogen will be required during the development, testing, and operation of these rocket engines.Better approaches are needed to simplify sensor integration and help reduce life-cycle costs. 1.Smarter sensors. Sensor integration should be a matter of "plug-and-play" making sensors easier to add to a system. Sensors that implement new standards can help address this problem; for example, IEEE STD 1451.4 defines transducer electronic data sheet (TEDS) templates for commonly used sensors such as bridge elements and thermocouples. When a 1451.4 compliant smart sensor is connected to a system that can read the TEDS memory, all information needed to configure the data acquisition system can be uploaded. This reduces the amount of labor required and helps minimize configuration errors. 2.Intelligent sensors. Data received from a sensor be scaled, linearized; and converted to engineering units. Methods to reduce sensor processing overhead at the application node are needed. Smart sensors using low-cost microprocessors with integral data acquisition and communication support offer the means to add these capabilities. Once a processor is embedded, other features can be added; for example, intelligent sensors can make a health assessment to inform the data acquisition client when sensor performance is suspect. 3.Distributed sample synchronization. Networks of sensors require new ways for synchronizing samples. Standards that address the distributed timing problem (for example, IEEE STD 1588) provide the means to aggregate samples from many distributed smart sensors with sub-microsecond accuracy. 4. Reduction in interconnect. Alternative means are needed to reduce the frequent problems associated with cabling and connectors. Wireless technologies offer the promise of reducing interconnects and simultaneously making it easy to quickly add a sensor to a system.

Lansaw, John↗

NASA NTRS2009

Integrated System Health Management Development Toolkit

This software toolkit is designed to model complex systems for the implementation of embedded Integrated System Health Management (ISHM) capability, which focuses on determining the condition (health) of every element in a complex system (detect anomalies, diagnose causes, and predict future anomalies), and to provide data, information, and knowledge (DIaK) to control systems for safe and effective operation.

Figueroa, Jorge↗

NASA NTRS2008

Compliance and Functional Testing of IEEE 1451.1 for NCAP-to-NCAP Communications in a Sensor Network

Distributed control in a networked environment is an irreplaceable feature in systems with remote sensors and actuators. Although distributed control was not originally designed to be networked, usage of off-the-shelf networking technologies has become so prevalent that control systems are desired to have access mechanisms similar to computer networks. However, proprietary transducer interfaces for network communications and distributed control overwhelmingly dominate this industry. Unless the lack of compatibility and interoperability among transducers is resolved, the mature level of access (that computer networking can deliver) will not be achieved in such networked distributed control systems. Standardization of networked transducer interfaces will enable devices from different manufacturers to talk to each other and ensure their plug-and-play capability. One such standard is the suite of IEEE 1451 for sensor network communication and transducer interfaces. The suite not only provides a standard interface for smart transducers, but also outlines the connection of an NCAP (network capable application processor) and transducers (through a transducer interface module TIM). This paper presents the design of the compliance testing of IEEE 1451.1 (referred to as Dot1) compatible NCAP-to-NCAP communications on a link-layer independent medium. The paper also represents the first demonstration of NCAP-to-NCAP communications with Dot1 compatibility: a tester NCAP and an NCAP under test (NUT).

Figueroa, Jorge↗

NASA NTRS2006

Intelligent Sensors and Components for On-Board ISHM

A viewgraph presentation on the development of intelligent sensors and components for on-board Integrated Systems Health Health Management (ISHM) is shown. The topics include: 1) Motivation; 2) Integrated Systems Health Management (ISHM); 3) Intelligent Components; 4) IEEE 1451; 5)Intelligent Sensors; 6) Application; and 7) Future Directions

Figueroa, Jorge↗

NASA NTRS2004

Strain-Gauge Measurement of Weight of Fluid in a Tank

A method of determining the amount of fluid in a tank is based on measurement of strains induced in tank supports by the weight of the fluid. Unlike most prior methods, this method is nonintrusive: there is no need to insert instrumentation in the tank and, hence, no need to run wires, cables, or tubes through the tank wall. Also unlike most prior methods, this method is applicable even if the fluid in the tank is at supercritical pressure and temperature, because it does not depend on the presence of a liquid/gas interface (as in liquid-level-measuring methods). The strain gauges used in this method may be of two types: foil and fiber-optic. Four foil gauges (full bridge) are mounted on each of the tank-supporting legs. As the tank is filled or emptied, the deformation in each leg increases or decreases, respectively. Measured deformations of all legs are added to obtain a composite deformation indicative of the change in weight of the tank plus fluid. An initial calibration is performed by recording data at two points (usually, empty and full) for which the mass or weight of fluid is known. It is assumed that the deformations are elastic, so that the line passing through the two points can be used as a calibration curve of mass (or weight) of fluid versus deformation. One or more fiber-optic gauges may be used instead of the foil gauges. The resolution of the fiber-optic and foil gauges is approximately the same, but the fiber-optic gauges are immune to EMI (electromagnetic interference), are linear with respect to temperature over their entire dynamic range (as defined by the behavior of the sample), and measure thermally induced deformations as predictable signals. Conversely, long term testing has demonstrated that the foil gauges exhibit an erratic behavior whenever subjected to direct sun radiation (even if protected with a rubberized cover). Henceforth, for deployment in outdoor conditions, fiber-optic gauges are the only option if one is to rely on the system for an extended period of time when a recalibration procedure may not be acceptable. A set of foil gauges had been tested on the supports of a 500-gallon (1,900-liter) tank. The gauges were found to be capable of measuring the deformations (up to 22 micro-strain) that occurred during filling and emptying of the tank. The fluid masses calculated from the gauge readings were found to be accurate within 4.5 percent. However, the reliability of the foil gauges over a few hours was not acceptable. Therefore, the foil sensor system is acceptable for use only in controlled environments (complete shade, or indoors).

Figueroa, Jorge↗

NASA NTRS2003

Strain-Gauge Measurement of Weight of Fluid in a Tank

A method of determining the amount of fluid in a tank is based on measurement of strains induced in tank supports by the weight of the fluid. Unlike most prior methods, this method is nonintrusive: there is no need to insert instrumentation in the tank and, hence, no need to run wires, cables, or tubes through the tank wall. Also unlike most prior methods, this method is applicable even if the fluid in the tank is at supercritical pressure and temperature, because it does not depend on the presence of a liquid/gas interface (as in liquid-level-measuring methods). The strain gauges used in this method are of two types: foil and fiber-optic. Four foil gauges and one or more fiber-optic gauges are mounted on each of the tank-supporting legs. An additional fiber-optic gauge is mounted on an object, made of the same material as that of the tank-supporting legs, that is not subjected to any mechanical load. The reading obtained by the additional fiber-optic gauge is used to compensate for apparent strains caused by changes in temperature. The signals from the foil and fiber-optic gauges are conditioned, then digitized for input to a computer. As the tank is filled or emptied, the deformation in each leg increases or decreases, respectively. Measured deformations of all legs are added to obtain a composite deformation indicative of the change in weight of the tank plus fluid. An initial calibration is performed by recording data at two points (usually, empty and full) for which the mass or weight of fluid is known. It is assumed that the deformations are elastic, so that the line passing through the two points can be used as a calibration curve of mass (or weight) of fluid versus deformation. At the time of reporting the information for this article, a set of foil gauges had been tested on the supports of a 500-gallon (1,900-liter) tank. The gauges were found to be capable of measuring the deformations (up to 22 microstrain) that occurred during filling and emptying the tank. The fluid masses calculated from the gauge readings were found to be accurate within 4.5 percent. It has been estimated that once the fiber-optic gauges are put into operation, it should be possible to determine fluid masses with 3 percent or less. It may be possible to increase accuracy further by increasing the signal-to-noise ratio through the use of more deformable tank supporting legs.

Figueroa, Jorge↗