Results for “PILOT” — Page 29

NASA NTRS2020

Flight Simulation Scenarios for Commercial Pilot Training and Crew State Monitoring

NASA Langley researchers addressed the Commercial Aviation Safety Team Safety Enhancement 211 through a series of studies to address "Attention-related Human Performance Limiting States" which include channelized attention, diverted attention, startle/surprise, and confirmation bias. The present report focuses on the development of improved training scenarios for operationally realistic Line-Oriented Flight Training scenarios. Areas addressed in the report include: (1) Highlights of events in the LOFT scenario used; (2) Interesting findings with implications for simulator motion; (3) Eye-tracking heat maps in proximity to failure events; (4) Researcher observations of crews as test subjects versus a pilot and a research team co-pilot; and (5) The results of a follow-up questionnaire completed by pilot participants regarding their usual training as well as the scenarios employed in the SHARP studies. These pilot ratings and comments are of value to simulation training developers.

James R. Comstock, Jr.↗

NASA NTRSDate not supplied

UAS Pilot Performance Comparisons with Different Low Size, Weight and Power Sensor Ranges

The present study evaluated the performance of UAS pilots under four simulated low size, weight, and power (SwaP) sensor ranges: 1.5nmi, 2.0nmi, 2.5nmi, and 3.0nmi. Nine active-duty UAS pilots responded to scripted DAA conflicts against non-cooperative intruders while flying a simulated RQ-7 Shadow at varied speeds along a pre-filed flight path in Class E airspace. Findings revealed a linear effect of sensor range on alerting time and separation performance, with nearly every DAA well clear (DWC) violation and all Near Mid-Air Collision (NMAC) events occurring below 2.5nmi. Response time differences at these reduced ranges were negligible due to the high frequency of warning-level alerts that require an immediate response. Since caution alert duration was truncated to some degree by each tested declaration range, pilots were often unable to coordinate their avoidance maneuvers with ATC prior to their uploads. Nonetheless, the 2.5nmi range allowed minimum alerting times that were sufficient for acceptable pilot performance. The study findings will inform DAA system requirements for UAS with alternative surveillance equipment and aircraft performance capabilities. Implications on DAA display and sensor requirements are discussed.

unmanned aircraft systems↗

NASA NTRSDate not supplied

UAS Pilot Performance Comparisons with Different Low Size, Weight and Power Sensor Ranges

The present study evaluated the performance of UAS pilots under four simulated low size, weight, and power (SwaP) sensor ranges: 1.5nmi, 2.0nmi, 2.5nmi, and 3.0nmi. Nine active-duty UAS pilots responded to scripted DAA conflicts against non-cooperative intruders while flying a simulated RQ-7 Shadow at varied speeds along a pre-filed flight path in Class E airspace. Findings revealed a linear effect of sensor range on alerting time and separation performance, with nearly every DAA well clear (DWC) violation and all Near Mid-Air Collision (NMAC) events occurring below 2.5nmi. Response time differences at these reduced ranges were negligible due to the high frequency of warning-level alerts that require an immediate response. Since caution alert duration was truncated to some degree by each tested declaration range, pilots were often unable to coordinate their avoidance maneuvers with ATC prior to their uploads. Nonetheless, the 2.5nmi range allowed minimum alerting times that were sufficient for acceptable pilot performance. These findings will inform DAA system requirements for UAS with alternative surveillance equipment and aircraft performance capabilities. Implications on DAA display and sensor requirements are discussed.

unmanned aircraft systems↗

NASA NTRS2020

UAS Pilot Performance Comparisons with Different Low Size, Weight and Power Sensor Ranges

The present study evaluated the performance of UAS pilots under four simulated low size, weight, and power (SwaP) sensor ranges: 1.5nmi, 2.0nmi, 2.5nmi, and 3.0nmi. Nine active-duty UAS pilots responded to scripted DAA conflicts against non-cooperative intruders while flying a simulated RQ-7 Shadow at varied speeds along a pre-filed flight path in Class E airspace. Findings revealed a linear effect of sensor range on alerting time and separation performance, with nearly every DAA well clear (DWC) violation and all Near Mid-Air Collision (NMAC) events occurring below 2.5nmi. Response time differences at these reduced ranges were negligible due to the high frequency of warning-level alerts that require an immediate response. Since caution alert duration was truncated to some degree by each tested declaration range, pilots were often unable to coordinate their avoidance maneuvers with ATC prior to their uploads. Nonetheless, the 2.5nmi range allowed minimum alerting times that were sufficient for acceptable pilot performance. These findings will inform DAA system requirements for UAS with alternative surveillance equipment and aircraft performance capabilities. Implications on DAA display and sensor requirements are discussed.

unmanned aircraft systems↗

NASA NTRSDate not supplied

Validation of Fitness for Duty Standards Using Pre- and Post-Flight Capsule Egress and Suited Functional Performance Tasks in Simulated Reduced Gravity (Pilot Egress Fitness)

As NASA prepares for exploration missions, it will be critical to understand and build upon known crew capabilities. Specifically, we need to know the functional capacities of crew at different stages of a mission and characterize these profiles so that the appropriate vehicle requirements and mission concepts of operations (ConOps) can be developed. One of the most complex phases of any missions is when there is a transition between gravity environments. For instance, both physiological adaptation to microgravity and subsequent re-entry into a gravity environment result in reduced functional capacity, even with rigorous adherence to inflight countermeasures. Quantification of the astronauts’ post-landing functional performance is necessary to design ConOps for exploration missions. Specifically, these two high-risk tasks may have to be performed soon after gravity transitions: •Unassisted capsule egress task after return to Earth •Planetary extravehicular activity (EVA) soon after landing on Mars or the Moon This study has been broken down into two phases. A pilot phase to assess the overall feasibility and demonstrate the capability to do these tasks shortly after landing and the full Egress Fitness study, which will be part of the CIPHER complement. This study uses a functional task approach to characterize performance of these high-risk tasks in long-duration ISS crewmembers before flight and shortly after return to Earth. Prior to any testing, each astronaut subject completes a suit fit check to ensure adequate sizing and mobility to be able to complete the EVA tasks. Pilot Egress Fitness pre-flight and post-flight testing includes an Earth based emergency egress out of a functional capsule mockup, and a short Mars gravity EVA simulation including suit donning, hatch egress, ladder descent, task board cable operations, baggage transfer over sand/rocky regolith, alignment with a rear entry port, and suit egress. Pre-flight testing can occur almost anytime pre-flight, but post-flight scheduling is much more critical with the capsule egress test occurring 1-4 hours after landing and the planetary EVA approximately 18-36 hours after landing. Data collected for both tasks includes task completion time, photo, and video. The EVA portion also includes collection of metabolic and heart rate. Pilot Egress Fitness study has completed baseline pre-flight testing on 3 astronaut subjects. Post-flight testing of the first two subjects will be completed in November 2021 and the final subject around March 2022. Results and lessons learned from this pilot study will inform the full Egress Fitness study, which will incorporate additional pre-flight sessions, longer EVA tasks, and post-flight testing on R+1, 4, and 7 to characterize the timeframe of recovery

J R Norcross↗

NASA NTRSDate not supplied

Development of the Mod II X-57 Piloted Simulator and Flying Qualities Predictions

This paper discusses the development of the X-57 Mod II piloted simulator along with the predicted flight dynamics of the airplane. The piloted simulator models were initially based on data published by Tecnam on a P2006T airplane but were further improved upon through parameter identification of flight data as well as modeling tools such as computational fluid dynamics. In addition to having accurate flight models, a realistic cockpit was constructed to aid pilot training. From the piloted simulator, an understanding of how the airplane will behave throughout the flight envelope using established FAR and MIL standards is discussed. Using the simulation results, this paper will show that the airplane is predicted to be statically and dynamically stable as well as having Level 1 flying qualities.

Ryan Wallace↗

NASA NTRSDate not supplied

An Approach to Identifying Aspects of Positive Pilot Behavior within the Aviation Safety Reporting System

The National Airspace System (NAS) is constantly evolving as air traffic continues to ramp up to pre-pandemic numbers and projected to grow to unprecedented levels in the coming years. As well as increasing demand to the current system, emerging operations such as Unmanned Autonomous Systems are also expected to add to complexity in the airspace. To address these issues, the industry and government agencies supporting the NAS will need to rely upon additional automation and new technologies to address future operational requirements, while continuing to be a world-leading safe transportation system. As these new technologies are implemented, the system continues to rely on human pilots and controllers in the loop to monitor the system and intervene in situations the automation cannot handle. The goal of proactively addressing safety is of foremost concern to ensure passenger confidence. The industry has implemented various Safety Monitoring Systems to identify safety risks and proactively address them before they result in a serious incident or accident. One such program is the Aviation Safety Reporting System (ASRS). ASRS is a long-established system where pilots and controllers voluntarily and anonymously report safety incidents they experienced and observed during line operations by providing rich text narratives describing the events, the environment, and conditions leading to the safety event of concern. These narratives provide insight and context around events of interest and can be used to identify emerging problems. They can trigger investigations within Flight Operational Quality Assurance or Flight Data Monitoring programs. However, this process typically focuses on the adverse events and the unsafe aspects of the operations surrounding the reported or detected events. This perspective of investigating factors that went wrong around an adverse event is commonly referred to as Safety I. Alternatively, characterizing successful actions that operators perform every day under varying conditions that keep the system within safe operating bounds is a concept referred to as Safety II. The benefit of the Safety II view is that the scope is much larger than that of Safety I since a vast majority of the operations result in successful flights. Many of the successful techniques used to manage operational threats are not documented in standard operating procedures or taught during training. They are typically acquired over time by working with experienced pilots during line operations or in many cases after experiencing a problem for the first time and reacting to it in situ, drawing from years of experience to manage the threat. In an attempt to quantify these positive actions, we are proposing an approach to extracting key behaviors within ASRS reports that can support the Safety II concept. Our analysis assumes that ASRS reports contain some descriptions of corrective actions that operators performed to prevent a situation from leading to an accident. Leveraging recent advances in Natural Language Process modeling, we have developed an approach to extract positive sentiment from reports, embed these positive statements in a vector space where they can be numerically analyzed, and clustering these statements into similar contextual categories. From these contextualized categories we can attempt to summarized and distilled aspects of the positive behavior. The goal is to identify categories of behavior that describe consistent operator techniques that supports the Safety II concept. With this information, airlines may enable learning from these positive actions, or address procedures that need to be changed to avoid having pilots implement a workaround. These insights can provide a lens into what is “going right” in the operations that may otherwise not be known widely within the community. It is envisioned that this approach can be extended to other narrative programs such as Line Operation Safety Audit or Learning Improvement Team reports where similar observed behavior can be analyzed to extract positive actions and inform the overall operations.

NLP↗

NASA NTRSDate not supplied

An Approach to Identifying Aspects of Positive Pilot Behavior within the Aviation Safety Reporting System

The National Airspace System (NAS) is constantly evolving as air traffic continues to ramp up to pre-pandemic numbers and projected to grow to unprecedented levels in the coming years. As well as increasing demand to the current system, emerging operations such as Unmanned Autonomous Systems are also expected to add to complexity in the airspace. To address these issues, the industry and government agencies supporting the NAS will need to rely upon additional automation and new technologies to address future operational requirements, while continuing to be a world-leading safe transportation system. As these new technologies are implemented, the system continues to rely on human pilots and controllers in the loop to monitor the system and intervene in situations the automation cannot handle. The goal of proactively addressing safety is of foremost concern to ensure passenger confidence. The industry has implemented various Safety Monitoring Systems to identify safety risks and proactively address them before they result in a serious incident or accident. One such program is the Aviation Safety Reporting System (ASRS). ASRS is a long-established system where pilots and controllers voluntarily and anonymously report safety incidents they experienced and observed during line operations by providing rich text narratives describing the events, the environment, and conditions leading to the safety event of concern. These narratives provide insight and context around events of interest and can be used to identify emerging problems. They can trigger investigations within Flight Operational Quality Assurance or Flight Data Monitoring programs. However, this process typically focuses on the adverse events and the unsafe aspects of the operations surrounding the reported or detected events. This perspective of investigating factors that went wrong around an adverse event is commonly referred to as Safety I. Alternatively, characterizing successful actions that operators perform every day under varying conditions that keep the system within safe operating bounds is a concept referred to as Safety II. The benefit of the Safety II view is that the scope is much larger than that of Safety I since a vast majority of the operations result in successful flights. Many of the successful techniques used to manage operational threats are not documented in standard operating procedures or taught during training. They are typically acquired over time by working with experienced pilots during line operations or in many cases after experiencing a problem for the first time and reacting to it in situ, drawing from years of experience to manage the threat. In an attempt to quantify these positive actions, we are proposing an approach to extracting key behaviors within ASRS reports that can support the Safety II concept. Our analysis assumes that ASRS reports contain some descriptions of corrective actions that operators performed to prevent a situation from leading to an accident. Leveraging recent advances in Natural Language Process modeling, we have developed an approach to extract positive sentiment from reports, embed these positive statements in a vector space where they can be numerically analyzed, and clustering these statements into similar contextual categories. From these contextualized categories we can attempt to summarized and distilled aspects of the positive behavior. The goal is to identify categories of behavior that describe consistent operator techniques that supports the Safety II concept. With this information, airlines may enable learning from these positive actions, or address procedures that need to be changed to avoid having pilots implement a workaround. These insights can provide a lens into what is “going right” in the operations that may otherwise not be known widely within the community. It is envisioned that this approach can be extended to other narrative programs such as Line Operation Safety Audit or Learning Improvement Team reports where similar observed behavior can be analyzed to extract positive actions and inform the overall operations.

NLP↗

NASA NTRSDate not supplied

An Approach to Identifying Aspects of Positive Pilot Behavior within the Aviation Safety Reporting System

The National Airspace System (NAS) is constantly evolving as air traffic continues to ramp up to pre-pandemic numbers and projected to grow to unprecedented levels in the coming years. As well as increasing demand to the current system, emerging operations such as Unmanned Autonomous Systems are also expected to add to complexity in the airspace. To address these issues, the industry and government agencies supporting the NAS will need to rely upon additional automation and new technologies to address future operational requirements, while continuing to be a world-leading safe transportation system. As these new technologies are implemented, the system continues to rely on human pilots and controllers in the loop to monitor the system and intervene in situations the automation cannot handle. The goal of proactively addressing safety is of foremost concern to ensure passenger confidence. The industry has implemented various Safety Monitoring Systems to identify safety risks and proactively address them before they result in a serious incident or accident. One such program is the Aviation Safety Reporting System (ASRS). ASRS is a long-established system where pilots and controllers voluntarily and anonymously report safety incidents they experienced and observed during line operations by providing rich text narratives describing the events, the environment, and conditions leading to the safety event of concern. These narratives provide insight and context around events of interest and can be used to identify emerging problems. They can trigger investigations within Flight Operational Quality Assurance or Flight Data Monitoring programs. However, this process typically focuses on the adverse events and the unsafe aspects of the operations surrounding the reported or detected events. This perspective of investigating factors that went wrong around an adverse event is commonly referred to as Safety I. Alternatively, characterizing successful actions that operators perform every day under varying conditions that keep the system within safe operating bounds is a concept referred to as Safety II. The benefit of the Safety II view is that the scope is much larger than that of Safety I since a vast majority of the operations result in successful flights. Many of the successful techniques used to manage operational threats are not documented in standard operating procedures or taught during training. They are typically acquired over time by working with experienced pilots during line operations or in many cases after experiencing a problem for the first time and reacting to it in situ, drawing from years of experience to manage the threat. In an attempt to quantify these positive actions, we are proposing an approach to extracting key behaviors within ASRS reports that can support the Safety II concept. Our analysis assumes that ASRS reports contain some descriptions of corrective actions that operators performed to prevent a situation from leading to an accident. Leveraging recent advances in Natural Language Process modeling, we have developed an approach to extract positive sentiment from reports, embed these positive statements in a vector space where they can be numerically analyzed, and clustering these statements into similar contextual categories. From these contextualized categories we can attempt to summarized and distilled aspects of the positive behavior. The goal is to identify categories of behavior that describe consistent operator techniques that supports the Safety II concept. With this information, airlines may enable learning from these positive actions, or address procedures that need to be changed to avoid having pilots implement a workaround. These insights can provide a lens into what is “going right” in the operations that may otherwise not be known widely within the community. It is envisioned that this approach can be extended to other narrative programs such as Line Operation Safety Audit or Learning Improvement Team reports where similar observed behavior can be analyzed to extract positive actions and inform the overall operations.

NLP↗

NASA NTRSDate not supplied

Helicopter Pilot Evaluations of the Airborne Collision Avoidance System Xr in a High-Fidelity Motion Simulation

New aircraft and aerial Urban Air Mobility operations require updated technologies to maintain vehicle separation during flight. Specifically, higher-density airspace will need more than traditional air traffic control to keep vehicles well clear of each other and avoid Near Midair Collisions. In response, the Federal Aviation Administration is currently developing the Airborne Collision Avoidance System X (ACAS X) for next-generation air traffic deconfliction, which provides caution-level and warning-level alerts in response to multiple aircraft types. This study recruited six helicopter pilots to fly an electric vertical takeoff and landing vehicle model in simulated operations under Visual Flight Rules (VFR). Flights were accomplished using the high-fidelity Vertical Motion Simulator at the NASA Ames Research Center. Participants controlled the vehicle using two side inceptors and foot rudders. The rotorcraft variant of ACAS X (ACAS Xr) was provided for alerting and guidance during traffic conflicts. Pilots used this system while giving feedback to the researchers through questionnaires, debriefs, and other discussions. Variables of interest to the study were phases of flight (i.e., Cruise, Hover, and Approach) and ACAS Xr configurations: The Collision Avoidance System configuration behaves similarly to current commercial traffic systems used for tactical deconfliction in crewed vehicles, and the Detect and Avoid configuration was developed to provide extra, corrective-level guidance for unmanned aircraft systems. Results showed that pilots found the alerting and guidance from ACAS Xr useful, effective, and acceptable for VFR operations. Certain elements, like speed guidance and text banners, were found to be of no use to the pilots. Hover and Approach scenarios were considered the most difficult for ACAS Xr alerting. Reasons for this difficulty were partially due to learning interference (i.e., overcoming previously learned behavior) and partially due to the vehicle model (i.e., NASA’s Lift Plus Cruise design). Still, alerting-based confounds reveal the need for more development for ACAS Xr during these Hover and Approach flight phases. Study caveats and future projects are discussed.

air taxis↗

NASA NTRSDate not supplied

Helicopter Pilot Evaluations of the Airborne Collision Avoidance System Xr in a High-Fidelity Motion Simulation

New aircraft and aerial Urban Air Mobility operations require updated technologies to maintain vehicle separation during flight. Specifically, higher-density airspace will need more than traditional air traffic control to keep vehicles well clear of each other and avoid Near Midair Collisions. In response, the Federal Aviation Administration is currently developing the Airborne Collision Avoidance System X (ACAS X) for next-generation air traffic deconfliction, which provides caution-level and warning-level alerts in response to multiple aircraft types. This study recruited six helicopter pilots to fly an electric vertical takeoff and landing vehicle model in simulated operations under Visual Flight Rules (VFR). Flights were accomplished using the high-fidelity Vertical Motion Simulator at the NASA Ames Research Center. Participants controlled the vehicle using two side inceptors and foot rudders. The rotorcraft variant of ACAS X (ACAS Xr) was provided for alerting and guidance during traffic conflicts. Pilots used this system while giving feedback to the researchers through questionnaires, debriefs, and other discussions. Variables of interest to the study were phases of flight (i.e., Cruise, Hover, and Approach) and ACAS Xr configurations: The Collision Avoidance System configuration behaves similarly to current commercial traffic systems used for tactical deconfliction in crewed vehicles, and the Detect and Avoid configuration was developed to provide extra, corrective-level guidance for unmanned aircraft systems. Results showed that pilots found the alerting and guidance from ACAS Xr useful, effective, and acceptable for VFR operations. Certain elements, like speed guidance and text banners, were found to be of no use to the pilots. Hover and Approach scenarios were considered the most difficult for ACAS Xr alerting. Reasons for this difficulty were partially due to learning interference (i.e., overcoming previously learned behavior) and partially due to the vehicle model (i.e., NASA’s Lift Plus Cruise design). Still, alerting-based confounds reveal the need for more development for ACAS Xr during these Hover and Approach flight phases. Study caveats and future projects are discussed.

air taxis↗

DOE OSTI2014

ISO 50001 for Commercial Buildings: Lessons Learned From U.S. DOE Pilot Project: Preprint

In the U.S., the ISO 50001 Standard, which establishes energy management systems (EnMSs) and processes, has shown uptake primarily in the industrial sector. The U.S. Department of Energy (DOE) undertook a pilot program to explore ISO 50001 implementation in commercial buildings. Eight organizations participated as pilots, with technical assistance provided by DOE, the National Renewable Energy Laboratory (NREL), the Lawrence Berkeley National Laboratory (LBNL), and the Georgia Institute of Technology (Georgia Tech). This paper shares important lessons learned from the pilot. Staff time was the most critical resource required to establish effective EnMSs in commercial buildings. The pilot also revealed that technical support and template/example materials were essential inputs. Crucial activities included evaluating performance, identifying goals, making connections, communicating operational controls, and tracking/reviewing progress. Benefits realized included enhanced intra-organizational connections, greater energy awareness, increased process efficiencies, and improved ability to make business cases. Incremental benefits for ISO 50001 certification were greater accountability, assurance of best practices, public relations opportunities, and potential to unlock verified savings credits or incentive money. Incremental certification costs included more staff/consultant time, money for certification, and a tendency to limit EnMS scope in order to ensure favorable audit results. Five best practices were identified - utilizing expert technical assistance, training, and other resources; focusing on implementation over documentation; keeping top management involved; considering organizational structure when selecting EnMS scope; and matching the implementation level to an EnMS's scope and scale. The last two practices are particularly relevant to the commercial buildings sector.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2014

SkyMine Carbon Mineralization Pilot Project

This Topical Report addresses accomplishments achieved during Phase 2b of the SkyMine® Carbon Mineralization Pilot Project. The primary objectives of this project are to design, construct, and operate a system to capture CO2 from a slipstream of flue gas from a commercial coal-fired cement kiln, convert that CO2 to products having commercial value (i.e., beneficial use), show the economic viability of the CO2 capture and conversion process, and thereby advance the technology to the point of readiness for commercial scale demonstration and deployment. The overall process is carbon negative, resulting in mineralization of CO2 that would otherwise be released into the atmosphere. The project will also substantiate market opportunities for the technology by sales of chemicals into existing markets, and identify opportunities to improve technology performance and reduce costs at the commercial scale. The project is being conducted in two phases. The primary objectives of Phase 1 were to evaluate proven SkyMine® process chemistry for commercial pilot-scale operation and complete the preliminary design for the pilot plant to be built and operated in Phase 2, complete a NEPA evaluation, and develop a comprehensive carbon life cycle analysis. The objective of Phase 2b was to build the pilot plant to be operated and tested in Phase 2c.

Christenson, Norm↗

DOE OSTI2015

Building America Case Study: Whole-House Solutions for Existing Homes: Greenbelt Homes, Inc. Pilot Retrofit Program; Whole-House Solutions for Existing Homes, Energy Efficiency & Renewable Energy (EERE)

In the fall of 2010, a multiyear pilot energy efficiency retrofit project was undertaken by Greenbelt Homes, Inc, (GHI) a 1,566 home cooperative of circa 1930 and 1940 homes in Greenbelt, Maryland. GHI established this pilot project to serve as a basis for decision making for the rollout of a decade-long community-wide upgrade program that will incorporate energy efficiency improvements to the building envelope and mechanical equipment. With the community upgrade fully funded by the cooperative through their membership without outside subsidies, this project presents a unique opportunity to evaluate and prioritize the wide-range of benefits of high-performance retrofits based on member experience with and acceptance of the retrofit measures implemented during the pilot project. Addressing the complex interactions between benefits, trade-offs, construction methods, project management implications, realistic upfront costs, financing, and other considerations, serves as a case study for energy retrofit projects to include high-performance technologies based on the long-term value to the homeowner. The pilot project focused on identifying the added costs and energy savings benefits of improvements. Phase 1: baseline evaluation for a representative set of 28 homes sited in seven buildings; Phase 2: installation of the building envelope improvements and continued monitoring of the energy consumption for the heating season and energy simulations supporting recommendations for HVAC and water heating upgrades to be implemented in Phase 3.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2015

Existing Whole-House Solutions Case Study: Greenbelt Homes, Inc. Pilot Retrofit Project

In the fall of 2010, a multiyear pilot energy efficiency retrofit project was undertaken by Greenbelt Homes, Inc., (GHI) a 1,566 home cooperative of circa 1930 and 1940 homes in Greenbelt, Maryland. GHI established this pilot project to serve as a basis for decision making for the rollout of a community-wide upgrade program that will incorporate energy efficiency improvements to the building envelope and mechanical equipment. With the community upgrade fully funded by the cooperative through their membership without outside subsidies, this project presents a unique opportunity to evaluate and prioritize the wide range of benefits of high-performance retrofits based on member experience with and acceptance of the retrofit measures implemented during the pilot project. Addressing the complex interactions between benefits, trade-offs, construction methods, project management implications, realistic upfront costs, financing, and other considerations, serves as a case study for energy retrofit projects that include high-performance technologies based on the long-term value to the homeowner. The pilot project focused on identifying the added costs and energy-savings benefits of improvements. Phase 1—baseline evaluation for a representative set of 28 homes sited in seven buildings; Phase 2—installation of the building envelope improvements and continued monitoring of the energy consumption for the heating season; Phase 3—energy simulations supporting recommendations for HVAC and water heating upgrades.

Attic↗

DOE OSTI2019

"250 kWt Pilot Testing in Support of a 10 MWe Coal-Direct Chemical Looping Demonstration Feasibility Study

The Babcock & Wilcox Company and The Ohio State University are developing iron-based metal oxide chemical looping technology for power generation and conversion of fossil fuels to chemicals and liquid fuels. A 250 kWt pilot facility has been constructed at the Babcock & Wilcox Research Center in Barberton, Ohio. Testing was conducted on the facility to support scale-up of the technology for implementation in a 10 MWe coal direct chemical looping large pilot plant at Dover Light & Power in Dover, Ohio. The paper discusses the results of the pilot test and the impact of the results on the design of the large pilot facility.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2019

250 kWth Pilot Testing in Support of a 10 MWe Coal-Direct Chemical Looping Demonstration Feasibility Study

The Coal-Direct Chemical Looping (CDCL) process is emerging as a promising technology capable of high efficiency for producing electricity with low cost for carbon capture. In the CDCL process, coal is fully combusted to form carbon dioxide (CO2) and water via reaction with Fe2O3-based oxygen-carrier particles in a moving-bed reducer reactor. During reaction with coal, the Fe2O3 is reduced to form a mixture of Fe and FeO. The reduced particles are then transported to the combustor reactor where they are re-oxidized with air. The oxidation of the Fe and FeO mixture generates heat that can be used to produce steam for power generation. Once the particles are fully regenerated, they are pneumatically recycled to the reducer reactor where another reduction-oxidation (Redox) cycle begins. The Babcock & Wilcox Company (B&W) and The Ohio State University (OSU) have been developing the CDCL technology based on iron-based metal oxide particles circulating in a moving-bed reducer coupled with an entrained-flow combustor. As part of a Phase I effort of a DOE-sponsored project, B&W identified scale-up technology gaps for the coal-direct chemical looping reactor process, most of which fall under the moving-bed reactor design and operation. However, after the Phase I research, B&W concluded that the CDCL technology has the potential of generating electricity while meeting the DOE goals of greater than 90% CO2 capture and less than 35% increase in levelized cost of electricity (LCOE). B&W then moved to a Phase II project to design, build and demonstrate the CDCL technology at a 250 kWth capacity. B&W finished the construction and commissioning of the pilot test facility in 2017. The approach used to design a 250 kWth pilot-scale CDCL facility to investigate the technology gaps is presented. Important lessons from the commissioning activities that would transfer to commercial plant start-up are also shared. The findings from the test program are being incorporated into a Pre-FEED study for a 10 MWe large pilot demonstration. Under a separately-funded heat integration project, B&W and OSU are developing a multiphase computational fluid dynamic model (MFIX) of the combustor to quantify heat transfer to embedded steam generation surface, utilizing pinch analysis (ASPEN Energy Analyzer) to identify potential improvements of the heat integration scheme, and developing an integrated dynamic model (ProTRAX) of the steam turbine coupled with the chemical looping process to identify potential start-up and transient operation issues. Under an advanced control system for optimizing operation, B&W is supporting OSU to install a rules-based optimizer (B&W’s FocalPoint) on their 25 kWt bench-scale facility on the OSU West Campus. Finally, B&W and OSU were recently selected to perform a Phase I Feasibility study to evaluate installation of the 10 MWe pilot at the Dover Power & Light Municipal Power Plant in Dover, Ohio. The feasibility study includes compiling an Environmental Information Volume and generating a cost estimate for the design, construction and commissioning of the plant as well as lining up commitments from potential project participants and funding contributors. Updates on each project will be presented. The status of the technology development will be discussed. We focus on the progress made to date towards closing the technology gaps under each project.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2019

From Theory to Practice: Lessons Learned from an Advanced M&V Commercial Pilot

Advanced measurement & verification (M&V), or M&V 2.0, is an energy data analysis method using advanced metering infrastructure (AMI) data in combination with analytics to quantify energy efficiency project savings. Advanced M&V is viewed as an enabler for underutilized behavioral, retrocommissioning, and holistic multi-measure efficiency efforts, as quantifying savings for these programs with existing methods has typically been very challenging. Despite its promise, there are still several unanswered questions about the use of advanced M&V such as: How accurately can these tools quantify energy savings? How can advanced M&V satisfy regulatory requirements for rigorous savings estimates? Where and how does advanced M&V intersect with traditional impact evaluation and the principles of ‘embedded’ evaluation, measurement & verification (EM&V)? Pilots are being pursued in various regions and program contexts to address these research questions. However, results from these pilots are rarely made public, meaning that lessons may not be widely shared and the scope of analyses varies widely. The paper presents encouraging results from a recent advanced M&V pilot and discusses key process-related aspects such as managing AMI data and refining analysis methodologies. An approach to reviewing and classifying projects based on savings characteristics and magnitude is demonstrated, as a potential risk management tool. The authors also demonstrate how advanced M&V can identify underperforming projects and non-routine events in a timely manner. The paper also outlines lessons learned from this and other recent pilot activity and barriers to be overcome in moving toward the goal of widespread adoption of holistic meter-based programs.

Crowe, Eliot↗