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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.

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At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A computational parametric study of ducted fuel injection implementation in a heavy-duty diesel engine

Experiments have shown that ducted fuel injection (DFI) effectively reduces soot emissions from direct-injection diesel engines. Although many computational studies have evaluated DFI’s spray development and soot reduction mechanisms in constant volume chambers, only limited computational work on internal combustion engines exists. The DFI duct assembly changes the engine’s in-cylinder flow, spray, and combustion development. Therefore, current production engine designs might not be optimal for achieving the best engine performance with DFI. Here, this work conducted an extensive numerical study to evaluate how parameter changes affect DFI performance. The parameters include swirl ratio, piston geometry, compression ratio (CR), number of injector orifices, split injection strategy, and exhaust gas recirculation (EGR) in a heavy-duty diesel engine utilizing DFI. The combustion and soot emission data from the Sandia compression ignition optical research engine were used for model validation. Simulations showed that an increased swirl ratio resulted in more intense jet flame-piston interaction, slowing down the combustion heat release during the late combustion stage and leading to lower indicated thermal efficiency (ITE) due to higher exhaust losses. A piston-bowl design with a reentrant inner piston edge yielded the highest thermal efficiency, due to the reduced cylinder head heat transfer loss. Additional injector orifices led to higher efficiency owing to a more advanced combustion phasing. Nevertheless, the maximum pressure rise rate (MPRR) and oxides of nitrogen (NO x ) emissions also increased with the number of injector orifices due to more rapid heat release and higher combustion temperature. Implementation of a split injection strategy combined with a higher EGR rate effectively inhibited the excessive MPRR and NO x formation. In general, the study concluded that DFI is not sensitive to most parameter changes but will benefit from future parameter optimization.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Moving small files in a networked environment

Globally distributed computing infrastructures, such as clouds and supercomputers, are currently used to manage data that is generated with an unprecedented speed from a variety of resources. Coping with this trend, the volume of data exchanged across distant sites increases substantially. To accelerate data transfer, high-speed networks are provided to connect remote sites. Most existing data movement solutions are optimized for moving large files. However, it is still challenging to transfer a large number of small files across networks. This disadvantage not only lowers data transfer performance, but also decreases overall system utilization. Here, we identify that moving small files is mainly constrained by degraded file system throughput, not just network performance as might be suspected. We have built a data transfer pipeline model to analyze the impact of small network I/O and storage I/O on data movement. Extending one of the widely used open source data movement solutions, GridFTP, we demonstrate several appropriate engineering approaches that mitigate the bottleneck and increase data transfer efficiency. We show optimizations that improve data transfer performance more than 5 times. In comparison to existing solutions, our approaches can save a significant amount of system resources for moving lots of small files.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Mitigating life cycle GHG emissions of roads to be built through 2030: Case study of a Chinese province

We report the expansion of road networks in emerging economies such as China causes significant greenhouse gas (GHG) emissions. This development is conflicting with China's commitment to achieve carbon neutrality. Thus, there is a need to better understand life cycle emissions of road infrastructure and opportunities to mitigate these emissions. Existing impact studies of roads in developing countries do not address recycled materials, improved pavement maintenance, or pavement-vehicle interaction and electric vehicle (EV) adoption. Combining firsthand information from Chinese road construction engineers with publicly available data, this paper estimates a comprehensive account of GHG emissions of the road pavement network to be constructed in the next ten years in the Shandong province in Northern China. Further, we estimate the potential of GHG emission reductions achievable under three scenario sets: maintenance optimization, alternative pavement material replacement, and EV adoption. Results show that the life cycle GHG emissions of highways and Class 1–4 roads to be constructed in the next 10 years amount to 147 Mt CO2-eq. Considering the use phase in our model reveals that it is the dominant stage in terms of emissions, largely due to pavement-vehicle interaction. Vehicle electrification can only moderately mitigate these emissions. Other stages, such as materials production and road maintenance and rehabilitation, contribute substantially to GHG emissions as well, highlighting the importance of optimizing the management of these stages. Surprisingly, longer, not shorter maintenance intervals, yield significant emission reductions. Another counter-intuitive finding is that thicker and more material-intensive pavement surfaces cause lower emissions overall. Taken together, optimal maintenance and rehabilitation schedules, alternative material use, and vehicle electrification provide GHG reduction potentials of 11%, 4%–16% and 2%–6%, respectively.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

System modeling for grid-interactive efficient building applications

Despite the abundance of research applications of system modeling in grid-interactive efficient buildings (GEBs), the transfer of those applications to real-world practices is still in its early stages. This is partially due to the lack of a summary on how system modeling should be established for a given application of GEBs. Here, we fill this gap by providing an extensive survey of the literature on system modeling for different GEBs that have been produced in the past decade. This survey involves over 300 relevant journal articles from the building community, the power system community, and the society of control. Specifically, we first identified key requirements of system modeling for GEBs based on various types of applications discussed in those publications. We then summarized the system modeling applications from those publications, in terms of their assumptions, modeling approach, and simulation. After that, we analyzed different assumptions made for various applications, the extent to which those modeling approaches satisfied the key requirements, and how those approaches can be scaled up for large-scale applications, which are quite common in GEBs. In addition, we gave insights on how to use system modeling for different applications in GEBs. At the end, we provided recommended directions for future studies to fully unleash the potentials of system modeling to support GEBs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

A discrete integral transform for rapid spectral synthesis

Accurate synthetic spectra that rely on large Line-By-Line (LBL)-databases are used in a wide range of applications such as high temperature combustion, atmospheric re-entry, planetary surveillance and laboratory plasmas. Conventionally synthetic spectra are calculated by computing a lineshape for every spectral line in the database and adding those together, which may take multiple hours for large databases. In this paper we propose a new approach for spectral synthesis based on an integral transform: the synthetic spectrum is calculated as the integral over the product of a Voigt profile and a newly proposed three-dimensional “lineshape distribution function”, which is a function of spectral position and Gaussian- & Lorentzian width coordinates. A fast discrete version of this transform based on the Fast Fourier Transform (FFT) is proposed, which improves performance compared to the conventional approach by several orders of magnitude while maintaining accuracy. Strategies that minimize the discretization error are discussed. A Python implementation of the method is compared against state-of-the-art spectral code RADIS, and is since adopted as RADIS's default synthesis method. The synthesis of a benchmark CO2 spectrum consisting of 1.8 M spectral lines and 200k spectral points took only 3.1 s using the proposed method (1011 lines × spectral points/s), a factor ~300 improvement over the state-of-the-art, with the relative improvement generally increasing for higher number of lines and/or number of spectral points. Finally, an experimental GPU-implementation of the method was also benchmarked, which demonstrated another 2~3 orders performance increase, achieving up to 5 ∙ 10 14 lines × spectral points/s.

42 ENGINEERING↗
DOE OSTI2017

Phosphoketolase overexpression increases biomass and lipid yield from methane in an obligate methanotrophic biocatalyst

Microbial conversion of methane to high-value bio-based chemicals and materials offers a path to mitigate GHG emissions and valorize this abundant-yet -underutilized carbon source. In addition to fermentation optimization strategies, rational methanotrophic bacterial strain engineering offers a means to reach industrially relevant titers, carbon yields, and productivities of target products. The phosphoketolase pathway functions in heterofermentative bacteria where carbon flux through two sugar catabolic pathways to mixed acids (lactic acid and acetic acid) increases cellular ATP production. Importantly, this pathway also serves as an alternative route to produce acetyl-CoA that bypasses the CO 2 lost through pyruvate decarboxylation in the Embden-Meyerhof-Parnas pathway. Thus, the phosphoketolase pathway can be leveraged for carbon efficient biocatalysis to acetyl-CoA-derived intermediates and products. Here, we show that the industrially promising methane biocatalyst, Methylomicrobium buryatense , encodes two phosphoketolase isoforms that are expressed in methanol- and methane-grown cells. Overexpression of the PktB isoform led to a 2-fold increase in intracellular acetyl-CoA concentration, and a 2.6-fold yield enhancement from methane to microbial biomass and lipids compared to wild-type, increasing the potential for methanotroph lipid-based fuel production. Off-gas analysis and metabolite profiling indicated that global metabolic rearrangements, including significant increases in post-translational protein acetylation and gene expression of the tetrahydromethanopterin-linked pathway, along with decreases in several excreted products, coincided with the superior biomass and lipid yield observed in the engineered strain. Further, these data suggest that phosphoketolase may play a key regulatory role in methanotrophic bacterial metabolism. As a result, given that acetyl-CoA is a key intermediate in several biosynthetic pathways, phosphoketolase overexpression offers a viable strategy to enhance the economics of an array of biological methane conversion processes.

09 BIOMASS FUELS↗
DOE OSTI2022

Accelerating manufacturing for biomass conversion via integrated process and bench digitalization: a perspective

We present a perspective for accelerating biomass manufacturing via digitalization. We summarize the challenges for manufacturing and identify areas where digitalization can help. A profound potential in using lignocellulosic biomass and renewable feedstocks, in general, is to produce new molecules and products with unmatched properties that have no analog in traditional refineries. Discovering such performance-advantaged molecules and the paths and processes to make them rapidly and systematically can transform manufacturing practices. Furthermore, we discuss retrosynthetic approaches, text mining, natural language processing, and modern machine learning methods to enable digitalization. Laboratory and multiscale computation automation via active learning are crucial to complement existing literature and expedite discovery and valuable data collection without a human in the loop. Such data can help process simulation and optimization select the most promising processes and molecules according to economic, environmental, and societal metrics. We propose the close integration between bench and process scale models and data to exploit the low dimensionality of the data and transform the manufacturing for renewable feedstocks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Automatic outdoor monitoring system for photovoltaic panels

Long-term acquisition of solar panel performance parameters, for panels operated at maximum power point in their real environment, is of critical importance in the photovoltaic research sector. However, few options exist for the characterization of non-standard panels such as concentrated photovoltaic systems, heavily soiled or shaded panels or those operating under non-standard spectral illumination; certainly, it is difficult to find such a measurement system that is flexible and affordable enough to be adopted by the smaller research institutes or universities. We present here an instrument aiming to fill this gap, autonomously tracking and maintaining any solar panel at maximum power point while continuously monitoring its operational parameters and dissipating the produced energy without connection to the power grid. Here, the instrument allows periodic acquisition of current-voltage curves to verify the employed maximum power point tracking approach. At the same time, with hardware schematics and software code being provided, it provides a flexible open development environment for the monitoring of non-standard generators like concentrator photovoltaic systems and to test novel power tracking approaches. The key issues, and the corresponding solutions, encountered in the design are analyzed in detail and the relevant schematics presented.

14 SOLAR ENERGY↗
DOE OSTI2017

Swit_4259, an acetoacetate decarboxylase-like enzyme from Sphingomonas wittichii RW1

The Gram-negative bacterium Sphingomonas wittichii RW1 is notable for its ability to metabolize a variety of aromatic hydrocarbons. Not surprisingly, the S. wittichii genome contains a number of putative aromatic hydrocarbon-degrading gene clusters. One of these includes an enzyme of unknown function, Swit_4259, which belongs to the acetoacetate decarboxylase-like superfamily (ADCSF). Here, it is reported that Swit_4259 is a small (28.8 kDa) tetrameric ADCSF enzyme that, unlike the prototypical members of the superfamily, does not have acetoacetate decarboxylase activity. Structural characterization shows that the tertiary structure of Swit_4259 is nearly identical to that of the true decarboxylases, but there are important differences in the fine structure of the Swit_4259 active site that lead to a divergence in function. In addition, it is shown that while it is a poor substrate, Swit_4259 can catalyze the hydration of 2-oxo-hex-3-enedioate to yield 2-oxo-4-hydroxyhexanedioate. It is also demonstrated that Swit_4259 has pyruvate aldolase-dehydratase activity, a feature that is common to all of the family V ADCSF enzymes studied to date. The enzymatic activity, together with the genomic context, suggests that Swit_4259 may be a hydratase with a role in the metabolism of an as-yet-unknown hydrocarbon. These data have implications for engineering bioremediation pathways to degrade specific pollutants, as well as structure–function relationships within the ADCSF in general.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Training Efforts in the Exascale Computing Project

This article delineates the training activities carried out under the auspices of the U.S. Department of Energy’s (DOE) Exascale Computing Project (ECP). While some of these activities are specific to members of ECP, others can be beneficial to the community at large. Additionally, we report on training opportunities and resources that the broad Computer Science and Engineering (CS&E) community can tap into; we seek to increase awareness about these resources, which we expect to go beyond ECP’s scope and life cycle.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

A Cast of Thousands: How the IDEAS Productivity Project Has Advanced Software Productivity and Sustainability

Computational and data-enabled science and engineering are revolutionizing advances throughout science and society, at all scales of computing. For example, teams in the U.S. Department of Energy’s Exascale Computing Project have been tackling new frontiers in modeling, simulation, and analysis by exploiting unprecedented exascale computing capabilities—building an advanced software ecosystem that supports next-generation applications and addresses disruptive changes in computer architectures. However, concerns are growing about the productivity of the developers of scientific software. Members of the Interoperable Design of Extreme-scale Application Software project serve as catalysts to address these challenges through fostering software communities, incubating and curating methodologies and resources, and disseminating knowledge to advance developer productivity and software sustainability. This article discusses how these synergistic activities are advancing scientific discovery—mitigating technical risks by building a firmer foundation for reproducible, sustainable science at all scales of computing, from laptops to clusters to exascale and beyond.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Transactive Control of Commercial Buildings for Demand Response

Transactive control is a type of distributed control strategy that uses market mechanism to engage self-interested responsive loads to achieve power balance in the electrical power grid. In this paper, we propose a transactive control approach of commercial building Heating, Ventilation, and Air- Conditioning (HVAC) systems for demand response. We first describe the system models, and identify their model parameters using data collected from Systems Engineering Building (SEB) located on our Pacific Northwest National Laboratory (PNNL) campus. We next present a transactive control market structure for commercial building HVAC system, and describe its agent bidding and market clearing strategies. Several case studies are performed in a simulation environment using Building Control Virtual Test Bed (BCVTB) and calibrated SEB EnergyPlus model. We show that the proposed transactive control approach is very effective at peak clipping, load shifting, and strategic conservation for commercial building HVAC systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

Energy System and Thermoeconomic Analysis of Combined Heat and Power High Temperature Proton Exchange Membrane Fuel Cell Systems for Light Commercial Buildings

The United States (U.S.) Department of Energy (DOE)’s Pacific Northwest National Laboratory (PNNL) is spearheading a program with industry to deploy and independently monitor five kilowatt-electric (kWe) combined heat and power (CHP) fuel cell systems (FCSs) in light commercial buildings. This publication discusses results from PNNL’s research efforts to independently evaluate manufacturer-stated engineering, economic, and environmental performance of these CHP FCSs at installation sites. The analysis was done by developing parameters for economic comparison of CHP installations. Key thermodynamic terms are first defined, followed by an economic analysis using both a standard accounting approach and a management accounting approach. Key economic and environmental performance parameters are evaluated, including (1) the average per unit cost of the CHP FCSs per unit of power, (2) the average per unit cost of the CHP FCSs per unit of energy, (3) the change in greenhouse gas (GHG) and air pollution emissions with a switch from conventional power plants and furnaces to CHP FCSs; (4) the change in GHG mitigation costs from the switch; and (5) the change in human health costs related to air pollution. From the power perspective, the average per unit cost per unit of electrical power is estimated to span a range from $15–19,000/ kilowatt-electric (kWe) (depending on site-specific changes in installation, fuel, and other costs), while the average per unit cost of electrical and heat recovery power varies between $7,000 and $9,000/kW. From the energy perspective, the average per unit cost per unit of electrical energy ranges from $0.38 to $0.46/kilowatt-hour-electric (kWhe), while the average per unit cost per unit of electrical and heat recovery energy varies from $0.18 to $0.23/kWh. These values are calculated from engineering and economic performance data provided by the manufacturer (not independently measured data). The GHG emissions were estimated to decrease by one-third by shifting from a conventional energy system to a CHP FCS system. The GHG mitigation costs were also proportional to the changes in the GHG gas emissions. Human health costs were estimated to decrease significantly with a switch from a conventional system to a CHP FCS system.

CHP↗