Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Comprehension”

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 397 records · Page 22

A Comprehensive Strategy for Grid Forming Control in DC Coupled Photovoltaic and Battery Energy Storage Inverters

This paper presents an integrated DC-DC and DCAC grid-forming control strategy for DC-coupled photovoltaic (PV) plus battery energy storage systems, considering the effect of DC link voltage variations caused by direct PV connections. A power reference algorithm determines power distribution between the PV and battery to the grid while observing device power ratings to prevent the over-rating of components and keep the battery's state of charge within an acceptable range. The simulated utility-scale model in MATLAB/Simulink illustrates its ability against extreme phase angle variation contingencies in the grid while controlled through grid-forming control with a fast dynamic on DC link voltage. The simulation results confirm the effectiveness of the proposed control in integrating PV plus battery configurations with grid forming control and maintaining reliable grid operation under severe grid disturbances.

battery, boost, control, energy storage, grid form↗

Fundamentals of Three-Terminal Tandem Solar Cells: a Comprehensive Taxonomy

Three-terminal tandem (3TT) solar cells can overcome some of the limitations of two- and four-terminal tandem designs. However, the coupled nature of the cells adds a degree of complexity to the devices themselves and the ways that their performance can be measured and reported. To facilitate understanding, we have developed a taxonomy which encompasses all types of 3TT devices, enabling a common nomenclature for discussing devices and performance. Once the physical devices, contact nodes, and loading circuitry have been self-consistently described, it becomes apparent that a wide range of 3TT devices share a common set of design and operating principles.

3T↗

A Comprehensive Model for Analyzing the Effects of Power Outages on Customers

Power outages can cause significant inconveniences to critical services and substantial economic losses. Therefore, it is crucial to systematically analyze the impact on customers during power outages caused by various factors, such as severe thunderstorms, floods, vegetation, or mechanical problems, and to plan for reliable operation and control under such events. Power outages in different locations may exhibit varying characteristics regarding customer impact. In this paper, we present a mathematical model that captures the essential characteristics of customer impact during power outages. The parameters of our model include impact duration, recovery duration, maximum impact level, increase curve parameter, and decrease curve parameter. We demonstrate how historical power outage data can be fitted to our model, enabling a systematic comparison of outages caused by different factors in various locations.

Lee, Sangkeun (Matt) [ORNL] (ORCID:000000021317511↗

Comprehensive framework for assessing and optimizing existing research networks

Conservation, monitoring, and research networks, or collections of ecological research sites unified under a common mission of data collection or a research mission, are essential infrastructure for understanding large landscapes. However, most networks developed opportunistically over decades rather than through systematic design, creating potential limitations in the ability to address conservation challenges across entire regions. We developed a framework to evaluate how well an existing research network represents the environmental conditions its members study and devised an approach to rank sites of priority for strategic expansion. Our approach measures performance through environmental representativeness, geographic coverage, and adequacy for scientific inference and thus optimizes limited monitoring resources to maximize scientific impact. We demonstrated this approach with the U.S. Department of Agriculture (USDA) Forest Service Experimental Forests and Ranges Network (EFRN), a 79‐site network across the United States that grew opportunistically over a century. At the national scale, the network effectively captured high‐biomass forests important for carbon cycle research; 82% of forest biomass was in well‐represented areas. Some areas in Texas, Florida, the Rocky Mountains, and the West Coast had no relevant EFRN sites, which limits the ability to make regional inferences. A fundamental challenge for the EFRN was that sites improving regional extent coverage sometimes provided minimal national benefits, which can create conflicts between local and global priorities. Adding the highest‐ranked candidate site provided a relevant site for 17% of currently poorly represented 1‐km pixel cells nationally, but regional and national site rankings varied considerably due to nested spatial inference. This framework provides quantitative tools for strategic infrastructure decision‐making, ensures that limited monitoring resources maximize conservation impact, and can be applied broadly to address the widespread challenge of optimizing conservation and monitoring networks worldwide.

additional site↗

Uncertainties in greenhouse gas emission factors: A comprehensive analysis of switchgrass‐based biofuel production

Abstract This study investigates uncertainties in greenhouse gas (GHG) emission factors related to switchgrass‐based biofuel production in Michigan. Using three life cycle assessment (LCA) databases—US lifecycle inventory (USLCI) database, GREET, and Ecoinvent—each with multiple versions, we recalculated the global warming intensity (GWI) and GHG mitigation potential in a static calculation. Employing Monte Carlo simulations along with local and global sensitivity analyses, we assess uncertainties and pinpoint key parameters influencing GWI. The convergence of results across our previous study, static calculations, and Monte Carlo simulations enhances the credibility of estimated GWI values. Static calculations, validated by Monte Carlo simulations, offer reasonable central tendencies, providing a robust foundation for policy considerations. However, the wider range observed in Monte Carlo simulations underscores the importance of potential variations and uncertainties in real‐world applications. Sensitivity analyses identify biofuel yield, GHG emissions of electricity, and soil organic carbon (SOC) change as pivotal parameters influencing GWI. Decreasing uncertainties in GWI may be achieved by making greater efforts to acquire more precise data on these parameters. Our study emphasizes the significance of considering diverse GHG factors and databases in GWI assessments and stresses the need for accurate electricity fuel mixes, crucial information for refining GWI assessments and informing strategies for sustainable biofuel production.

Kim, Seungdo↗

De novo transcriptome sequencing of Capsicum frutescens . L and comprehensive analysis of salt stress alleviating mechanism by Bacillus atrophaeus WU ‐9

Abstract Salt stress, as one of the most severe environmental stresses, can cause a series of changes in plants. However, the explanation of plant salt stress alleviating mechanism of plant growth–promoting rhizobacteria (PGPR) was hindered by the limited availability of transcriptomic information for salt stress‐treated plants grown in a microorganism‐controlled environment. Our previous reports have selected Bacillus atrophaeus WU‐9 as PGPR significantly alleviating pepper ( Capsicum frutescens . L) salt stress. In this work, the RNA‐seq analysis of salt stress‐treated and untreated plants, grown with and without WU‐9 in a microorganism‐controlled environment, was used to reveal the plant salt stress alleviating mechanisms of WU‐9. Twelve sequencing libraries, prepared by treating with WU‐9 and salt (150 mM NaCl for 36 h), were constructed by RNA‐Seq technique. Non‐inoculated seedlings mainly respond to salt stress through regulation of signal transduction, such as ethylene‐activated signaling pathway, signaling and cell communication, etc. And ethylene signal participated in salt stress response in pepper through regulating defense responses, fruit ripening and senescence. WU‐9 inoculation under salt stress mainly improves salt tolerance and plant growth by regulating salt stress‐responding ethylene and auxin signal transduction, utilization of proline, photosynthesis, antioxidant enzyme activities and cell enlargement. Furthermore, 86 differentially expressed genes and 20 transcription factors were identified as associated with salt stress response and tolerance. Thus, this innovative transcriptomic study identified the salt stress response and alleviation in C. frutescens . L with PGPR inoculation. This result provided novel insights into the salinity alleviation in pepper regulated by PGPR.

Wang, Wenfei↗

Reestablishing larval connectivity in an estuarine landscape: the importance of shoreline and subtidal oysters ( Crassostrea virginica ) in a comprehensive oyster restoration program

The decline of oyster reefs in estuaries has resulted from a combination of chronic and acute disturbances. The loss has resulted in decreased yield for the oyster fishery as well as a decline in ecological benefits that has led to increased efforts to restore oyster reefs. The need for scientific guidance in accomplishing these restoration goals has become even more pressing in the northcentral Gulf of Mexico in the wake of injury to oyster reefs resulting from the Deepwater Horizon oil spill. Restoration of both the shallow, marsh-fringing oyster aggregations and the deeper subtidal oyster reefs is necessary. Historically, fringing oysters have been overlooked in the oyster habitat landscape because of their limited commercial value. Here, we use a biophysical transport model to examine the transport and settlement of oyster larvae in known oyster reefs along the coast of the northcentral Gulf of Mexico. The modeling demonstrated that the majority of oyster larvae settle within the embayment (>98%) or sub-basin (>65%) of their origin. Additionally, the model demonstrated the importance of fringing oysters as a source of larvae to re-seed other fringing oysters along marsh edges as well as subtidal oyster reefs. We conclude that networks of reefs, including both fringing oyster habitat and subtidal oyster reefs within sub-basins, are necessary to provide resilience to the population at the sub-basin level. Finally, we conclude that fringing oyster habitat may serve as an archipelago-like network to enhance larval supply and connectivity for oysters throughout the mesosaline portions of estuaries.

ADCIRC↗

Comprehensive Studies on Hot Compaction and Vibration-Assisted Compaction Tests of Aluminum Powder

Abstract Aluminum powder compaction was studied using both test and simulation. Cold compaction, hot compaction, and vibration-assisted (cold) compaction tests were conducted to achieve different density ratios. First, the hot compaction test (at 300 °C, compression pressure 140 MPa) improved about 6% compared with cold compaction under the same compression pressure. Second, although the relative density ratio does not obviously improve at a vibration-assisted (cold) compaction, the strength of the specimens made under vibration loading is much better than those of cold compaction. Additionally, finite element models with well-calibrated Drucker–Prager Cap (DPC) material constitutive model were built in abaqus/standard to simulate the powder compaction process. The results of the finite element model have very good correlations with test results up to the tested range, and this finite element model further predicts the loading conditions needed to achieve the higher density ratios. Two exponential equations of the predicted density ratio were obtained by combining the test data and the simulation results. A new analytical solution was developed to predict the axial pressure versus the density ratio for the powder compaction according to DPC material model. The results between the analytical solution and the simulation model have a very good match.

Engineering↗

COnTORT: COmprehensive Transcriptomic ORganizational Tool for Simultaneously Retrieving and Organizing Numerous Gene Expression Data Sets from the NCBI Gene Expression Omnibus Database

We introduce COnTORT ( CO mprehensive T ranscriptomic OR ganizational T ool), a publicly available program that retrieves all available gene expression data and associated metadata for an organism from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database. The data are compiled into text files that can be used for downstream bioinformatic applications.

Myers, Kevin S.↗

mSphere of Influence: Comprehensive Genetic Analysis

Jason M. Peters works in the fields of antibiotic resistance and biofuel production. In this mSphere of Influence article, he reflects on how the paper “A global genetic interaction network maps a wiring diagram of cellular function” by Costanzo et al. (Science 353:aaf1420, 2016, https://doi.org/10.1126/science.aaf1420 ) has impacted his work by highlighting the power of gene networks to uncover new biology.

Peters, Jason M.↗

Comprehensive compartmental model and calibration algorithm for the study of clinical implications of the population-level spread of COVID-19: a study protocol

The complex dynamics of the coronavirus disease 2019 (COVID-19) pandemic has made obtaining reliable long-term forecasts of the disease progression difficult. Simple mechanistic models with deterministic parameters are useful for short-term predictions but have ultimately been unsuccessful in extrapolating the trajectory of the pandemic because of unmodelled dynamics and the unrealistic level of certainty that is assumed in the predictions. We propose a 22-compartment epidemiological model that includes compartments not previously considered concurrently, to account for the effects of vaccination, asymptomatic individuals, inadequate access to hospital care, post-acute COVID-19 and recovery with long-term health complications. Additionally, new connections between compartments introduce new dynamics to the system and provide a framework to study the sensitivity of model outputs to several concurrent effects, including temporary immunity, vaccination rate and vaccine effectiveness. Subject to data availability for a given region, we discuss a means by which population demographics (age, comorbidity, socioeconomic status, sex and geographical location) and clinically relevant information (different variants, different vaccines) can be incorporated within the 22-compartment framework. Considering a probabilistic interpretation of the parameters allows the model's predictions to reflect the current state of uncertainty about the model parameters and model states. We propose the use of a sparse Bayesian learning algorithm for parameter calibration and model selection. This methodology considers a combination of prescribed parameter prior distributions for parameters that are known to be essential to the modelled dynamics and automatic relevance determination priors for parameters whose relevance is questionable. This is useful as it helps prevent overfitting the available epidemiological data when calibrating the parameters of the proposed model. Population-level administrative health data will serve as partial observations of the model states.

59 BASIC BIOLOGICAL SCIENCES↗

Advancing Comprehension of Quantum Application Outputs: A Visualization Technique

Noise in quantum computers presents a challenge for the users of quantum computing despite the rapid progress we have seen in the past few years in building quantum computers. Existing works have addressed the noise in quantum computers using a variety of mitigation techniques since error correction requires a large number of qubits which is infeasible at present. One of the consequences of quantum computing noise is that users are unable to reproduce similar output from the same quantum computer at different times, let alone from various quantum computers. In this work, we have made initial attempts to visualize quantum basis states for all the circuits that were used in quantum machine learning from various quantum computers and noise-free quantum simulators. We have opened up a pathway for further research into this field where we will be able to isolate noisy states from non-noisy states leading to efficient error mitigation. This is where our work provides an important step in the direction of efficient error mitigation. Our work also provides a ground for quantum noise visualization in the case of large numbers of qubits.

Senapati, Priyabrata↗

A Comprehensive Numerical and Experimental Study for the Passive Thermal Management in Battery Modules and Packs

Cooling plates in battery packs of electric vehicles play critical roles in passive thermal management systems to reduce risks of catastrophic thermal runaway. In this work, a series of numerical simulations and experiments are carried out to unveil the role of cooling plates (both between cells and a bottom plate parallel to the cell stack) on the thermal behavior of battery modules and packs under nail penetrations. First, we investigated the role of side cooling plates on the thermal runaway propagation mitigation in battery modules (1S3P) and packs (3S3P) by varying the key parameters of the side cooling plates, such as plate thicknesses, thermal contact resistances, and materials. Then, three important factors for passive thermal management systems are identified: (i) thermal mass of side cooling plates, (ii) interfacial thermal contact resistances, and (iii) the effective heat transfer coefficients at exterior surfaces. The roles of bottom cooling plates on thermal runaway propagation mitigation in 1S3P and 1S5P battery modules are numerically investigated by comparing the thermal behavior of the modules with only side cooling plates and with both side and bottom cooling plates.

25 ENERGY STORAGE↗

Optimizing Energy For Delivery Drones - A Comprehensive Tool Set For Drone Energy Calculation And Drone Fleet Optimization

This tool is intended to be deployed for potential customers to compare the energy profiles across various drone types/classes. The primary factors considered were design of the drone, the weight of the drone, the weight of the payload, and how the drone is flown. It has energy comparison metrics like "Drone (A) vs Drone (B) ", "Drone vs Ground Vehicle", "Drone Energy from delivery via landing versus hovering". It also includes the ability to determine the number of drones and batteries needed to optimally deliver goods from a chosen location to a set of destinations.

Mendadhala, Rohit [Idaho National Laboratory (INL)↗