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This case study describes the installation process and resulting payback of rooftop solar PV systems on two multifamily apartment buildings in Washington, D.C. owned by WashREIT.
Mesoscale convective systems (MCSs) and isolated deep convection (IDC) significantly influence local weather conditions and the hydrological cycle across the United States. Their future changes under warming is critical to the society. However, the exact impacts of thermodynamic environmental changes on them are difficult to resolve using climate model simulations which integrate both dynamic and thermodynamic factors. This study explores a theoretical modeling approach to isolate environmental thermodynamic effects on their future changes through a case study. For a 50-day period during the 2020 summer, a pair of convection-permitting model simulations indicate contrasting changes in MCSs and IDC between inland and coastal regions under pseudo global warming. Driven by the thermodynamic environments of these simulations, a single-column parcel model indicates a decrease in the frequency of IDC occurrences, along with increases in duration and precipitation amount under warming, attributable to rising most unstable convective available potential energy (MUCAPE), convective inhibition (MUCIN), and precipitable water (PW). A multi-column parcel model reveals contrasting changes in the frequency and mean area of MCSs between inland and coastal regions, underscoring the increase in mean MUCIN over inland regions and increases in mean MUCAPE and PW over coastal regions. The increase in mean MCS area over inland regions is linked to the interplay between accelerated gust fronts and enhanced subsidence strength, which is further traced to the unchanged mean MUCIN but increased mean MUCAPE in large-scale environments. In conclusion, these case study results suggest a major role of thermodynamic environmental changes in controlling characteristics of MCSs and IDC under warming.
Zero liquid discharge (ZLD) systems installed at power facilities with the primary purpose of meeting water discharge regulations have the added benefit of providing high quality effluent that can be reused in the facility. This paper provides a review of water use in power sector recirculating cooling towers and a baseline assessment of on-site water reuse at natural gas combined cycle (NGCC) power facilities. Two NGCC facilities with reverse-osmosis (RO) or brine-concentrator processes followed by evaporation ponds were selected as case studies; data from these facilities were used to quantify the water, energy, and cost implications of implementing conventional and emerging ZLD technologies. At one case study facility, model results show that implementation of ZLD would reduce water withdrawals by 18%, which is less than savings associated with implementation of dry cooling but comparable to current efforts to reduce water withdrawals by increasing cycles of concentration. Implementation of ZLD using high-recovery RO resulted in a doubling of the levelized cost of water (LCOW). LCOW increased more when a brine concentrator was used. For both case studies, the ZLD system using high-recovery RO required less than 0.1% of a facilitiy's annual electricity generation and the ZLD system using a brine concentrator process required less than 0.8%. Additionally, increasing the evaporation pond area to minimize required ZLD system recovery rates and reduce system electricity costs does not reduce the LCOW. Instead, the LCOW increases because less water is recovered and more water is lost to evaporation. Furthermore, if water availability decreases or water competition/cost increases, facilities may be incentivized to maximize water recovery from ZLD systems.
Prior to the launch of the STS-132/ULF4 mission, the International Space Station (ISS) Flight Control Team was alerted to the approach of a space debris with a predicted time of closest approach approximately 1 hr after Space Shuttle docking. As a result, the ISS team considered performing a collision avoidance maneuver prior to the Space Shuttle s approach. The purpose of this presentation will be to use this case study to illustrate best practices of the human spaceflight trajectory operations team. The presentation will begin with an overview of the roles of the real-time ISS and Space Shuttle trajectory flight control teams. Then, the STS-132/ULF4 case study will be used to illustrate the issues and lessons learned involved in performing Space Shuttle rendezvous maneuver planning and execution. Specific elements of the STS-132 Space Shuttle rendezvous maneuver profile that can be used to provide mission assurance in cases of trajectory uncertainty will be described and discussed. Additionally, this case study will be used to provide context for identifying lessons learned in an operational environment that requires technical and decision-making coordination between two control center teams with two potentially maneuvering space vehicles.
Case‐crossover study designs are observational studies used to assess postmarket safety of medical products (eg, vaccines or drugs). As a case‐crossover study is self‐controlled, its advantages include better control for confounding because the design controls for any time‐invariant measured and unmeasured confounding and potentially greater feasibility as only data from those experiencing an event (or cases) are required. However, self‐matching also introduces correlation between case and control periods within a subject or matched unit. To estimate sample size in a case‐crossover study, investigators currently use Dupont's formula ( Biometrics 1988; 43 :1157‐1168), which was originally developed for a matched case‐control study. This formula is relevant as it takes into account correlation in exposure between controls and cases, which are expected to be high in self‐controlled studies. However, in our study, we show that Dupont's formula and other currently used methods to determine sample size for case‐crossover studies may be inadequate. Specifically, these formulas tend to underestimate the true required sample size, determined through simulations, for a range of values in the parameter space. We present mathematical derivations to explain where some currently used methods fail and propose two new sample size estimation methods that provide a more accurate estimate of the true required sample size.
In 2009, the U.S. Department of Energy under the American Recovery and Reinvestment Act (ARRA) awarded a grant to the Chattanooga, Tennessee, Electric Power Board (EPB) as part of the Smart Grid Investment Grant Program. The grant had the objective “to accelerate the transformation of the nation’s electric grid by deploying smart grid technologies.” This funding award enabled EPB to expedite the original smart grid implementation schedule from an estimated 10-12 years to 2.5 years. With this funding, EPB invested heavily in distribution automation technologies including installing over 1,200 automated circuit switches and sensors on 171 circuits. For utilities considering a commitment to distribution automation, there are underlying questions such as the following: “What is the value?” and “What are the costs?” This case study attempts to answer these questions. The primary benefit of distribution automation is increased reliability or reduced power outage duration and frequency. Power outages directly impact customer economics by interfering with business functions. In the past, this economic driver has been difficult to effectively evaluate. However, as this case study demonstrates, tools and analysis techniques are now available. In this case study, the impact on customer costs associated with power outages before and after the implementation of distribution automation are compared. Two example evaluations are performed to demonstrate the benefits: 1) a savings baseline for customers under normal operations1 and 2) customer savings for a single severe weather event. Cost calculations for customer power outages are performed using the US Department of Energy (DOE) Interruption Cost Estimate (ICE) calculator2. This tool uses standard metrics associated with outages and the customers to calculate cost impact. The analysis shows that EPB customers have seen significant reliability improvements from the implementation of distribution automation. Under normal operations, the investment in distribution automation has enabled a 43.5% reduction in annual outage minutes since 2012. This has led to an estimated total savings of $26.8 million per year. Examining a single severe weather event3, the distribution automation was able to restore power to 40,579 (nearly 56%) customers within 1–2 seconds and reduce outage minutes by 29.0%. This saved customers an estimated $23.2 million over the course of the storm.
This document is one of three offshore post-primary CO 2 enhanced oil recovery project case studies that compares the modeling results from an industry standard compositional simulator (“GEM”) and a variant of the FE/NETL CO 2 Prophet Model (CO 2 Prophet Model), which determined the CO 2 Prophet Model was able to reasonably represent the performance of the CO 2 flood modeled using the more sophisticated GEM. This case study uses the Petronius oil field J-2 Sand using a quarter of a five-spot pattern design (one CO 2 injector well and five production wells), for a 40-year injection scenario. A version of the CO 2 Prophet Model is available on NETL’s website under the Collection Name: FE/NETL CO 2 Prophet Model.
This document is one of three offshore post-primary CO 2 enhanced oil recovery project case studies that compares the modeling results from an industry standard compositional simulator (“GEM”) and a variant of the FE/NETL CO 2 Prophet Model (CO 2 Prophet Model), which determined the CO 2 Prophet Model was able to reasonably represent the performance of the CO 2 flood modeled using the more sophisticated GEM. This case study uses the Cognac oil field J Sand, in the field’s Northeast fault block, using a line drive pattern design (one CO 2 injector and two production wells), for 10-year and 20-year injection scenarios. A version of the CO 2 Prophet Model is available on NETL’s website under the Collection Name: FE/NETL CO 2 Prophet Model.
This document is one of three offshore post-primary CO 2 enhanced oil recovery project case studies that compares the modeling results from an industry standard compositional simulator (“GEM”) and a variant of the FE/NETL CO 2 Prophet Model (CO 2 Prophet Model), which determined the CO 2 Prophet Model was able to reasonably represent the performance of the CO 2 flood modeled using the more sophisticated GEM. This case study uses the Horn Mountain oil field NFB M Sand, in the field's North fault block, using three pairs of wells. Each pair of wells is a line drive pattern design (one CO 2 injector and one production well). Four 20-year injection scenarios were assessed, varying CO 2 injector well placements. A version of the CO 2 Prophet Model is available on NETL’s website under the Collection Name: FE/NETL CO 2 Prophet Model.
NREL has completed a series of detailed case studies comparing the simulations of the System Advisor Model (SAM) and measured performance data or published performance expectations. These case studies compare PV measured performance data with simulated performance data using appropriate weather data. The measured data sets were primarily taken from NREL onsite PV systems and weather monitoringstations.
In High Energy Physics (HEP), experimentalists generate large volumes of data that, when analyzed, helps us better understand the fundamental particles and their interactions. This data is often captured in many files of small size, creating a data management challenge for scientists. In order to better facilitate data management, transfer, and analysis on large scale platforms, it is advantageous to aggregate data further into a smaller number of larger files. However, this translation process can consume significant time and resources, and if performed incorrectly the resulting aggregated files can be inefficient for highly parallel access during analysis on large scale platforms. In this paper, we present our case study on parallel I/O strategies and HDF5 features for reducing data aggregation time, making effective use of compression, and ensuring efficient access to the resulting data during analysis at scale. We focus on NOvA detector data in this case study, a large-scale HEP experiment generating many terabytes of data. Here, the lessons learned from our case study inform the handling of similar datasets, thus expanding community knowledge related to this common data management task.
High initial cost and lack of public awareness of ground source heat pump (GSHP) technology are the two major barriers preventing rapid deployment of this energy saving technology in the United States. Under the American Recovery and Reinvestment Act (ARRA), 26 GSHP projects have been competitively selected and carried out to demonstrate the benefits of GSHP systems and innovative technologies for cost reduction and/or performance improvement. This paper highlights findings of a case study of one of the ARRA-funded GSHP demonstration projects, which is a heating only central GSHP system using shallow aquifer as heat source and installed at a warehouse and truck bay at Kalispell, MT. This case study is based on the analysis of measured performance data, utility bills, and calculations of energy consumptions of conventional central heating systems for providing the same heat outputs as the central GSHP system did. The evaluated performance metrics include energy efficiency of the heat pump equipment and the overall GSHP system, pumping performance, energy savings, carbon emission reductions, and cost-effectiveness of GSHP system compared with conventional heating systems. This case study also identified areas for reducing uncertainties in performance evaluation, improving operational efficiency, and reducing installed cost of similar GSHP systems in the future. Publication of ASHRAE at the annual conference in Seattle.
This design process error-proofing case study describes a design review practice implemented by a project manager at NASA Jet Propulsion Laboratory. There are many types of reviews at NASA: required and not, formalized and informal, programmatic and technical. Standing project formal reviews such as the Preliminary Design Review (PDR) and Critical Design Review (CDR) are a required part of every project and mission development. However, the engineering peer reviews that support teams technical work on such projects are often informal, ad hoc, and inconsistent across the organization. This case study discusses issues and innovations identified by a project manager at JPL and implemented in "engineering peer meetings" for his group.
This design process error-proofing case study describes a design review practice implemented by a project manager at NASA Jet Propulsion Laboratory. There are many types of reviews at NASA: required and not, formalized and informal, programmatic and technical. Standing project formal reviews such as the Preliminary Design Review (PDR) and Critical Design Review (CDR) are a required part of every project and mission development. However, the engineering peer reviews that support teams technical work on such projects are often informal, ad hoc, and inconsistent across the organization. This case study discusses issues and innovations identified by a project manager at JPL and implemented in 'engineering peer meetings' for his group.
The primary goal of the Consortium for the Advancement of Shape Memory Alloy Research and Technology (CASMART) is to enable the design of revolutionary applications based on shape memory alloy (SMA) technology. In order to help realize this goal and reduce the development time and required experience for the fabrication of SMA actuation systems, several modeling tools have been developed for common actuator types and are discussed herein along with case studies, which highlight the capabilities and limitations of these tools. Due to their ability to sustain high stresses and recover large deformations, SMAs have many potential applications as reliable, lightweight, solid-state actuators. Their advantage over classical actuators can also be further improved when the actuator geometry is modified to fit the specific application. In this paper, three common actuator designs are studied: wires, which are lightweight, low-profile, and easily implemented; springs, which offer actuation strokes upwards of 200 at reduced mechanical loads; and torque tubes, which can provide large actuation forces in small volumes and develop a repeatable zero-load actuation response (known as the two-way shape memory effect). The modeling frameworks, which have been implemented in the design tools, are developed for each of these frequently used SMA actuator types. In order to demonstrate the versatility and flexibility of the presented design tools, as well as validate their modeling framework, several design challenges were completed. These case studies include the design and development of an active hinge for the deployment of a solar array or foldable space structure, an adaptive solar array deployment and positioning system, a passive air temperature controller for regulation flow temperatures inside of a jet engine, and a redesign of the Corvette active hatch, which allows for pressure equalization of the car interior. For each of the presented case studies, a prototype or proof-of-concept was fabricated and the experimental results and lessons learned are discussed. This analysis presents a collection of CASMART collaborative best practices in order to allow readers to utilize the available design tools and understand their modeling principles. These design tools, which are based on engineering models, can provide first-order optimal designs and are a basic and efficient method for either demonstrating design feasibility or refining design parameters. Although the design and integration of an SMA-based actuation system always requires application- and environment-specific engineering considerations, common modeling tools can significantly reduce the investment required for actuation system development and provide valuable engineering insight.
High initial costs and lack of public awareness of ground-source heat pump (GSHP) technology are the two major barriers preventing rapid deployment of this energy-saving technology in the United States. Under the American Recovery and Reinvestment Act (ARRA), 26 GSHP projects have been competitively selected and carried out to demonstrate the benefits of GSHP systems and innovative technologies for cost reduction and/or performance improvement. This paper highlights the findings of a case study of one of the ARRA-funded GSHP demonstration projects, a ground-source variable refrigerant flow (GS-VRF) system installed at the Human Health Building at Oakland University in Rochester, Michigan. This case study is based on the analysis of measured performance data, maintenance records, construction costs, and simulations of the energy consumption of conventional central heating, ventilation, and air-conditioning (HVAC) systems providing the same level of space conditioning as the demonstrated GS-VRF system. The evaluated performance metrics include the energy efficiency of the heat pump equipment and the overall GS-VRF system, pumping performance, energy savings, carbon emission reductions, and cost-effectiveness of the GS-VRF system compared with conventional HVAC systems. This case study also identified opportunities for reducing uncertainties in the performance evaluation, improving the operational efficiency, and reducing the installed cost of similar GSHP systems in the future.
This presentation highlights the findings from two renewable energy case studies conducted by the Joint Institute for Strategic Energy Analysis (JISEA) for the Colorado Department of Agriculture and the Colorado Energy Office in 2021. The case studies; one exploring renewable energy integration for greenhouses and one evaluating biogas production potential for a dairy, illustrate the wide variety of renewable energy opportunities and the significant potential benefits of renewable energy in the agriculture sector in Colorado.
Software is becoming increasingly significant in today's critical avionics systems. To achieve safe, reliable software, government regulatory agencies such as the Federal Aviation Administration (FAA) and the Department of Defense mandate the use of certain software development methods. However, little scientific evidence exists to show a correlation between software development methods and product quality. Given this lack of evidence, a series of experiments has been conducted to understand why and how software fails. The Guidance and Control Software (GCS) project is the latest in this series. The GCS project is a case study of the Requirements and Technical Concepts for Aviation RTCA/DO-178B guidelines, Software Considerations in Airborne Systems and Equipment Certification. All civil transport airframe and equipment vendors are expected to comply with these guidelines in building systems to be certified by the FAA for use in commercial aircraft. For the case study, two implementations of a guidance and control application were developed to comply with the DO-178B guidelines for Level A (critical) software. The development included the requirements, design, coding, verification, configuration management, and quality assurance processes. This paper discusses the details of the GCS project and presents the results of the case study.