Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “CaSe”

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.

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

At least 361 records · Page 20

How Do Electricity Pricing Programs Impact the Selection of Energy Efficiency Measures? - A Case Study with U.S. Medium Office Buildings

Building owners usually select energy efficiency measures (EEMs) by referring to return on investment (ROI). Current studies tend to apply static energy price to estimate ROI. However, more and more buildings are adopting dynamic electricity pricing programs. To understand how electricity pricing programs impact the selection of EEMs, this paper presents an analysis of the ROIs of EEMs under different pricing programs using U.S. medium office buildings as an example. Eight EEMs in four typical cities are selected as case studies. Considering five electricity pricing programs scenarios (one static program and four dynamic programs), EEMs are selected based on their ROIs. The main findings are: (1) The ROIs of EEMs change under different pricing programs. (2) In Honolulu, Buffalo, and Denver, replacing interior fixtures with higher-efficiency fixtures has a significantly higher ROI than the rest EEMs under all five pricing programs. However, the ROI of this EEM in Honolulu ranges from 28% to 47% for different pricing programs. (3) Similarly, in Fairbanks, replace heating coil with higher-efficiency coil produce higher ROI than the rest under all five pricing programs. (4) For other EEMs, their ROI rankings vary according to electricity pricing programs.

demand response↗

Deploying advanced supervisory control strategies to small- and medium-sized commercial buildings: Case study and lessons learned

Deploying advanced supervisory control strategies (ASCSs) in small- and medium-sized commercial buildings (SMBs) is vital but faces two issues: (1) a lack of building control and communication infrastructure (BCCI) in SMBs and (2) the significant engineering efforts required to implement and configurate ASCSs. Despite hindering the large-scale adoption of ASCSs in SMBs, these issues have not been adequately explored in the literature, which tends to focus more on feasibility than scalability. This paper provides a comprehensive evaluation of these two issues through a case study of an occupied SMB in eastern Tennessee of the United States. Specifically, we design and implement a BCCI for the studied building with commercial off-the-shelf products to accommodate the needs for deploying ASCSs. Here, we then deploy two ASCSs—a rule-based setback control and a model predictive control (MPC)—with the BCCI and evaluate their performance throughout the summer of 2024. This study reveals that the main bottlenecks in establishing BCCIs for SMBs are the high initial cost (∼$56/m 2 ) and communication delays (up to 9 min). Additionally, the assessment of the two ASCSs indicates that the majority (∼75 %) of the engineering effort required for implementation and configuration is spent on model identification, debugging, and tuning.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Optimizing district energy systems under uncertainty: Insights from a case study from Washington D.C., USA

This study investigates solutions for delivering affordable heating and cooling to a brownfield site, focusing on a case study in Washington, DC. Moving towards more diverse and resilient energy systems, we identify the optimal portfolio for a district energy system with diverse energy sources to meet the area’s energy demands. Our methodological approach integrates two detailed models: one calculating building-level energy demand and the other optimizing district energy technology choices based on their demand profiles, accounting for uncertainties in energy prices, policies, and other parameters. The results provide an economic comparison of district and individual supply options at the building level, emphasizing the flexibility district systems can offer to the electricity sector. District energy systems demonstrate cost-stabilization benefits amidst volatile energy prices and external uncertainties. For heating, district systems yield significant cost savings compared to individual solutions, driven by fuel flexibility and the use of local renewable energy sources. For cooling, district systems also show advantages, though individual systems may remain more cost-effective for smaller buildings. Additionally, district systems exhibit considerable flexibility on the heating side, as evidenced by variations in electricity consumption. We recommend future research to explore the relationship between the economics of district energy systems, particularly at the building level, and their flexibility potential for the electricity sector across diverse geographic contexts to reduce overall grid costs and promote grid reliability. This includes areas with distinct zoning laws, municipal priorities, utility structures, and funding mechanisms, such as the United States, and regions like Europe with pronounced electricity price volatility.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Case study on the novel permitting and authorization of PacWave South, a US grid-connected wave energy test facility: Development, challenges, and insights

Marine energy (i.e., energy from waves, tides, currents, and rivers) in the United States is a nascent industry. In particular, permitting processes—an uncertainty for industry advancement that can be costly and time consuming to navigate—have rarely been tested and used for marine energy. The novelty of the marine energy industry and utilization of open ocean permitting processes that were not originally developed for marine energy have led to extensive efforts to gain consensus amongst state and federal regulatory agencies to authorize marine energy projects. In 2021, Oregon State University successfully completed permitting of a wave energy test facility, called PacWave South, off the coast of Oregon, which is designed to advance wave energy research and development. This article documents the multi-year process that Oregon State University used to receive federal and state authorization for a pre-permitted commercial-scale grid connected facility by detailing the development of the test facility, management of uncertainty and challenges, and key decisions. The PacWave South case study provides insights for the larger marine energy community as the industry advances towards commercialization.

16 TIDAL AND WAVE POWER↗

Risk to ecological resources following remediation can be due mainly to increased resource value of successful restoration: A case study from the Department of Energy's Hanford Site

Several nations are faced with the need to remediate large contaminated sites following World War II, the Cold War, and abandoned industrial sites, and to return them to productive land uses. In the United States, the Department of Energy (DOE) has the largest cleanup challenge, and its Hanford Site in the state of Washington has the most extensive and most expensive cleanup task. Ideally, the risk to ecological resources on remediation sites is evaluated before, during, and after remediation, and the risk from, or damage to, ecological resources from contaminants should be lower following remediation. In this paper, we report the risk to ecological resources before, during, and as a consequence of remediation on contaminated units requiring cleanup, and then examine the causes for changes in risk by evaluating 56 cleanup evaluation units (EUs) at the Hanford Site. In this case, remediation includes a restoration phase. In general, the risk to ecological and eco-cultural resources is currently not discernible or low at most contaminated units, increases during remediation, and decreases thereafter. Remediation often causes physical disruption to ecosystems as it reduces the risk from exposure to contaminants. Most new remediation projects at the Hanford Site include ecological restoration. Ecological restoration results in the potential for the presence of higher quality resources after remediation than currently exists on these contaminated lands and facilities. Although counter-intuitive, our evaluation of the risk to ecological resources following remediation indicated that a significant percentage of units (61%) will be at increased risk in the post-remediation period. This increased risk is due to DOE's successful remediation and restoration that results in a higher percent of native vegetation and higher ecological value on the sites in the post-remediation period than before. These newly-created resources can then be at risk from post-remediation activities. Risks to these new higher quality resources include the potential for spread of invasive species and of noxious grasses used in previous cleanup actions, disruption of ecosystems (including those with state or federally listed species and unique ecosystems), compaction of soil, use of pesticides to control invasive species, and the eventual need for continued monitoring activities. Thus, by greatly improving the existing habitat and health of eco-receptors, and maintaining habitat corridors between high quality habitats, the ecological resources in the post-remediated units are at risk unless care is taken to protect them. Many of the negative effects of both remediation and future monitoring (or other future land uses) can be avoided by planning and management early in the remediation process. We suggest DOE and other agencies convene a panel of managers, remediation scientists, regulators, environmental and ecological scientists, Native Americans, economists, and the public to develop a generic list of performance metrics for the restoration phase of remediation, including evaluation of success, which could be applied across the DOE complex.

54 ENVIRONMENTAL SCIENCES↗

Towards assessing the impact of anthropogenic sound on fishes: Gaps, perspectives, and a case study of a large floating bridge

Underwater anthropogenic sound can cause physical, physiological, and behavioral impacts on fishes. With the development of marine energy facilities, the impact of man-made underwater sound on fishes has become a growing regulatory concern. Large gaps remain in how to perform an underwater sound assessment. Such gaps mainly reside in scientific evidence, regulatory criteria, sound characterization metrics, sound field modeling, and instrumentation for field measurement. Here, this paper reviewed existing work on underwater sound assessment for fishes to identify critical gaps and provide perspectives on how to deal with these gaps, demonstrated with a case study on the impact of the Hood Canal Bridge traffic sound on migrating steelhead smolts in Washington State, U.S. We also provide perspectives on future research directions to bridge the identified gaps for aquatic ecological assessment.

59 BASIC BIOLOGICAL SCIENCES↗

The intrinsic value of bioblendstocks: Prenol as a case study

Decarbonizing the transportation sector is likely to require both electrification and increased incorporation of biofuels and/or bioblendstocks. While the social and environmental benefits of bioblendstocks are well understood, their real value for the fuel producers has not been established. As such, this work considers prenol as a bioblendstock case study to identify sources of intrinsic value to fuel blenders by studying the properties of binary mixtures with gasoline components. The considered refinery blendstocks were samples of full range naphthas from the distillation, fluidized catalytic cracking, isomerization, alkylation, and reforming units. Octane numbers, Reid vapor pressure, distillation curves, and sulfur content were evaluated. Our results indicate the need for adjusting the formulation of the base fuel, depending on the interplay among the properties of the bioblendstock and those of the base fuel. Prenol increased research octane number (RON) and octane sensitivity (OS) of the base fuel, by up to 25 and 10 octane numbers, respectively. Additionally, 10 vol% prenol reduced RVP up to 2.2 psi, for the more volatile blendstock. Thus, considering prenol as a low volatility, RON/OS boosting bioblendstock, the composition of the preferred base fuel was proposed as containing reduced olefins and aromatics, and increase light fractions. The potential impact of this new gasoline formulation on refining processes and products gives rise to direct sources of value to the refiners, such as exporting products to the chemicals market, increasing the value of intermediate refinery streams, decreasing operating severity of certain refinery units, and broadening of the product suite.

09 BIOMASS FUELS↗

Radiation Toxicity in Patients With Collagen Vascular Disease: A Meta-Analysis of Case-Control Studies

Several retrospective series have reported that patients with collagen vascular disease (CVD) are at increased risk of radiation (RT) toxicity. However, the evidence is mixed, and many series lack control groups. We performed a meta-analysis including only case-cohort or randomized studies that examined the risk of RT toxicity for patients with CVD compared with controls.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Impacts of climate change on future hurricane induced rainfall and flooding in a coastal watershed: A case study on Hurricane Harvey

The warming climate is likely to increase hurricane-associated extreme rainfall and lead to sea-level rise (SLR). Thus, how the floods induced by intense hurricanes respond to these potential changes is of great concern. This study investigates the future warmer climate impacts on hurricane-induced extreme rainfall, and—more importantly—the subsequent compound flooding at the watershed scale (from an event-based analysis perspective). To this goal, a modeling framework is designed based on the Distributed Hydrology Soil Vegetation Model (DHSVM), the Two-Dimensional fvand the Regional Community Earth System Model (R-CESM). The framework was applied to Hurricane Harvey (2017) at the Clear Creek watershed (a coastal watershed in the southern Houston) as a case study. The results show that the projected maximum rainfall totals over the watershed would be exacerbated by 17.7 % and 49.7 % in the 2050s and 2090s (respectively) under Representative Concentration Pathway 8.5 (RCP 8.5). This means a 16.1 % increase in Harvey rainfall over the watershed per degree Celsius increase in Mean Surface Temperature over the Gulf of Mexico region (18°~31° N, 77°~98° W). Meanwhile, the increases in maximum inundation extent would be 11.0 % (2050s) and 19.5 % (2090s). Furthermore, considerable increases in maximum inundation depth and duration in regions along the middle and downstream of Clear Creek (and also those around Clear Lake) are expected. The projected SLR will have little effect on the maximum inundation depth and extent if storm surge changes are not taken into account; meanwhile, it will influence the inundation duration at downstream locations. In conclusion, this modeling framework can be also applied at other coastal watersheds to evaluate the projected climate change impacts on the compound flooding induced by extreme climate events.

54 ENVIRONMENTAL SCIENCES↗

Physics-informed Bayesian machine learning case study: Integral blade rotors

This paper provides a physics-informed Bayesian machine learning (PIBML) description and case study. The PIBML approach applies three physics-based models to establish the initial beliefs before testing to determine the probability of milling stability (or prior). These include: receptance coupling substructure analysis (RCSA) prediction for the tool tip frequency response functions; finite element software prediction of the mechanistic force model coefficients; and a spindle speed-dependent power law model for process damping. Testing was then performed to identify optimal stable machining conditions using an expected improvement in material removal rate criterion. The prior probability of stability was updated using the test results to determine the posterior probability of stability. The test results were compared to the parameter recommendations provided by the endmill manufacturer. A demonstration integral blade rotor was machined at the optimal stable machining conditions for 304 stainless steel and 6061-T6 aluminum. Finally, the disagreement between manufacturer recommendations and milling performance in both materials tested emphasizes the need for broad implementation of PIBML approaches to increase machining productivity and efficiency.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Laser additive manufacturing for infrastructure repair: A case study of a deteriorated steel bridge beam

As our transportation infrastructure ages, its deterioration is becoming a growing concern. Rapid and effective methods for repair can reduce the need for time-and cost-intensive replacement of structures such as roadway bridges. In this work, laser-based additive manufacturing (AM) was developed for the re-pair of damaged beams in steel bridges. A corroded structural beam of low-carbon A36 steel was selected for this case study and 316L stainless steel was used for repair due to its excellent mechanical properties and corrosion resistance. Simulated repair experiments were performed on specimens extracted from the beam, and prepared with various groove shapes (Rectangular, Trapezoidal, and U-shaped). More in-depth parametric and microstructural studies were carried out with a series of U-shaped specimens repaired with the linear laser input energy varied from 19.5 to 30.0 J mm -1 . The tensile properties of the repaired specimens and interface structures were also investigated in detail. It was found that the repaired specimens had a slightly higher tensile strength despite a reduction in tensile elongation compared to the A36 steel base metal. The influence of interfacial microstructure and heterogeneity on the mechanical proper-ties of the repaired specimens was discussed. Furthermore, our work suggests the promising potential to employ AM for structural repair and provides fundamental insights into processing-structure-property relationships in laser AM-repaired materials.

36 MATERIALS SCIENCE↗

An uncertainty visualization framework for large-scale cardiovascular flow simulations: A case study on aortic stenosis

We present a generalizable uncertainty quantification (UQ) and visualization framework for lattice Boltzmann method simulations of high Reynolds number vascular flows, demonstrated on a patient-specific stenosed aorta. The framework combines EasyVVUQ for parameter sampling with large-eddy simulation turbulence modeling in HemeLB, and executes ensembles on the Frontier exascale supercomputer. Spatially resolved metrics, including entropy and isosurface-crossing probability, are used to map uncertainty in pressure and wall shear stress fields directly onto vascular geometries. Two sources of model variability are examined: inlet peak velocity and the Smagorinsky constant. Inlet velocity variation produces high uncertainty downstream of the stenosis where turbulence develops, while upstream regions remain stable. Smagorinsky constant variation has little effect on the large-scale pressure field but increases WSS uncertainty in localized high-shear regions. In both cases, the stenotic throat manifests low entropy, indicative of robust identification of elevated WSS. By linking quantitative UQ measures to three-dimensional anatomy, the framework improves interpretability over conventional 1D UQ plots and supports clinically relevant decision-making, with broad applicability to vascular flow problems requiring both accuracy and spatial insight.

Hemodynamics↗

An Accelerated Testing and Analysis Framework for Qualification of Battery Materials Part I: A Case Study with LFP Cathodes

The growing demand for batteries used within automotive, aviation, and grid applications has exacerbated the need to supplement critical battery material feedstocks, such as those for anode and cathode active materials. New or supplementary material sources, however, universally comprise unique properties that can affect the lifetime and performance of resultant batteries. Even minor differences between new sources and established supplies can delay qualification, making it difficult for new suppliers to commercialize and resulting in a less resilient supply chain. Accordingly, the influence of composition, microstructure, and morphology on electrochemical performance should be characterized quickly and accurately to accelerate commercialization of new sources. This work introduces a tiered framework to assess new material viability and understand the influence of physicochemical properties on battery performance. The Tier 1 testing described here is rapid and low-effort to recognize materials with fundamental flaws and potentially disqualify them. Later testing would require more effort but provide higher-fidelity information with a goal of application-based validation. A case study examining commercial sources of LiFePO4 (LFP) is presented, using Tier 1 of the protocol to identify rapid electrochemical and physicochemical signals that correlate with performance and provide early go/no-go decisions for LFP materials without requiring long-term cycling.

25 ENERGY STORAGE↗

Bayesian optimization for inverse calibration of expensive computer models: A case study for Johnson-Cook model in machining

Inverse model calibration for identifying the constitutive model parameters can be computationally demanding for expensive-to-evaluate simulation models. Here, this paper presents a modified Bayesian optimization (BO) method, denoted as BO-bound, that incorporates theoretical bounds on the quantity of interest. A case study for the inverse calibration of the Johnson Cook (J-C) flow stress model parameters is presented using machining (cutting) force data. The results show fast calibration of the five J-C parameters within 25 simulations. In general, the BO-bound method is applicable for inverse calibration of any expensive simulation models as well as optimization problems with known bounds.

Bayesian optimization↗

On the contribution of Pair Distribution Function (PDF) to the characterization of nanocrystalline MOFs: The case of M-MOF-74

Nanoporous Metal-Organic Frameworks (MOFs) have a great potential in so many industrial applications including heterogeneous catalysis and gas storage/capture/separation. MOF-74 is one of the most interesting MOFs in an academic context, as it contains open metal sites, possesses high versatility in metal nature, and can be prepared with so small crystal size. As a consequence, the catalytic activity of these nanocrystalline materials is superior to that given by their conventional counterparts. However, their characterization by conventional X-ray diffraction (XRD) is insufficient. Here, we present a joint study of XRD and Pair Distribution Function (PDF) -both acquired under synchrotron radiation- of a series of nanocrystalline M-MOF-74 materials (M = Mg, Co, Ni, Cu or Zn) prepared at room temperature. Whereas the XRD continues being lacking for an adequate structural characterization, PDF provides key structural information at medium and short range and, therefore, is ideal for studying such nano-domains. It was confirmed that these materials are exclusively composed by MOF-74 phase and that their poor ability to diffract is due solely to their eminent nanocrystallinity, which resulted to be even more pronounced than it has been previously estimated. Beyond Scherrer-like approaches, PDF can give direct information about the range of crystal size in nanocrystalline materials. Moreover, the technique is also able to detect slight structural deviations in short-range environments, just like it is made clear in the case of Cu-MOF-74 compared with the rest of M-MOF-74 materials, which possesses a marked Jahn-Teller effect in the octahedral coordination of Cu.

36 MATERIALS SCIENCE↗

Impact of boundary layer simulation on predicting radioactive pollutant dispersion: a case study for HANARO Research Reactor using the WRF-MMIF-CALPUFF modeling system

Wind plays an important role in cases of unexpected radioactive pollutant dispersion, deciding distribution and concentration of the leaked substance. The accurate prediction of wind has been challenging in numerical weather prediction models, especially near the surface because of the complex interaction between turbulent flow and topographic effect. As such, in this study, we investigated the characteristics of atmospheric dispersion of radioactive material (i.e. 137 Cs) according to the simulated boundary layer around the HANARO research nuclear reactor in Korea using the Weather Research and Forecasting (WRF)-Mesoscale Model Interface (MMIF)-California Puff (CALPUFF) model system. We examined the impacts of orographic drag on wind field, stability calculation methods, and planetary boundary layer parameterizations on the dispersion of radioactive material under a radioactive leaking scenario. We found that inclusion of the orographic drag effect in the WRF model improved the wind prediction most significantly over the complex terrain area, leading the model system to estimate the radioactive concentration near the reactor more conservatively. We also emphasized the importance of the stability calculation method and employing the skillful boundary layer parameterization to ensure more accurate low atmospheric conditions, in order to simulate more feasible spatial distribution of the radioactive dispersion in leaking scenarios.

54 ENVIRONMENTAL SCIENCES↗

Material Interactions in Severe Accidents – Benchmarking the MELCOR V2.2 Eutectics Model for a BWR-3 MARK-I Station Blackout: Part I – Single Case Analysis

Here in this analysis, the two material interaction models available in the MELCOR code are benchmarked for a severe accident at a BWR under representative Fukushima Daiichi boundary conditions. This part of the benchmark investigates the impact of each material interaction model on accident progression through a detailed single case analysis. It is found that the eutectics model simulation exhibits more rapid accident progression for the duration of the accident. The slower accident progression exhibited by the interactive materials model simulation, however, allows for a greater degree of core material oxidation and hydrogen generation to occur, as well as elevated core temperatures during the ex-vessel accident phase. The eutectics model simulation exhibits more significant degradation of core components during the late in-vessel accident phase – more debris forms and relocates to the lower plenum before lower head failure. The larger debris bed observed in the eutectics model simulation also reaches higher temperatures, presenting a more significant thermal challenge to the lower head until its failure. At the end of the simulated accident scenario, however, core damage is comparable between both simulations due to significant core degradation that occurs during the ex-vessel phase in the interactive materials model simulation. A key difference between the two models’ performance is the maximum temperatures that can be reached in the core and therefore the maximum ΔT between any two components. When implementing the interactive materials model, users have the option to modify the liquefaction temperature of the ZrO 2 -interactive and UO 2 -interactive materials as a way to mimic early fuel rod failure due to material interactions. Through modification of the liquefaction of high melting point materials with significant mass, users may inadvertently limit maximum core temperatures for fuel, cladding, and debris components.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Modeling, analysis, and optimization of complex nuclear processes and facilities via computational methods: The HALEU process case study

Improving and adapting industrial systems to timely meet changing programmatic and market demands is an important goal to achieve, including when operating and maintaining complex nuclear processes and facilities. However, changes to these complex systems are costly, particularly when they are already in place and bounded to stringent requirements and constraints such as when handling radioactive material and contaminated equipment. These conditions often exist when treating spent nuclear fuel remotely within shielded nuclear radiation chambers, commonly referred as hot cells, to condition nuclear material and/or fabricate products for utilization in other nuclear enterprises such as in the manufacture of advanced nuclear fuel. The illustrative case considered here is the production of high assay low enriched uranium (HALEU) products supporting the deployment of advanced nuclear reactors. For the HALEU program, resources invested were and are being systematically analyzed so that these investments are maximized in a facility that is nearly 60 years old. A methodology that has effectively enabled optimized and improvements in the Spent Fuel Treatment (SFT) program, and consequently the HALEU program, involves discrete event simulation as addressed in this article. Here, the quantification of multiple productivity metrics, including material processing rates, cycle times, bottlenecks, number of material transfers as well as equipment, workstation, and material handling utilization, has resulted in a myriad of diverse discoveries and data-informed decisions regarding process layout and constituent, labor levels and schedules, selection of new process units, storage needs, and other critical process configurations. This article describes such a computational capability being applied for decision-making, illustrates its application to an actual process and program, provides illustrative results, and argues how computational methods for the modeling, analysis, and optimization of complex processes and facilities does lead to informed decisions derived from data and not only from intuition.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗