Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “data reduction”

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 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Effect of Soil Properties and Input Motion on Site Amplification Using Validated Nonlinear Soil Model

Here, three-dimensional (3-D) nonlinear site response analyses are conducted using finite element models of actual soil profiles from ten nuclear power plant (NPP) sites in the United States to investigate the effects of soil properties and input motions on site amplification. The modeling approach developed in this study combines several novel elements, such as 3-D analysis (including vertical motions), nonlinear inelastic behavior of soil (strain-dependent shear modulus reduction and hysteretic damping), formulation of nonreflecting boundary conditions at the base, and generation of realistic outcrop ground motions for specific sites. All these elements of the modeling approach are first validated using actual data from five earthquakes at three downhole array stations recorded in the Kiban-Kyoshin network (KiK-net), Japan. The same approach is then used to develop site models of ten NPP sites in the United States and corresponding ground motions that are spectrally matched to the site hazard spectra. Eight sets of three-component input motions are used in the study and are categorized on the basis of presence or absence of a near-field pulse in the seed ground motions used for spectral matching. It is found that all sites retain a definite site amplification function regardless of the input motion, provided that the seed motion is spectrally matched to the site hazard spectra. The magnitude of site amplification and frequencies at which they occur depend upon soil properties, particularly the shear wave velocity profile and the constitutive relationship (strain-dependent shear modulus reduction and hysteretic damping) of soil. Amplification of spectral acceleration in the vertical direction (up-down motion) is found to be just as much as, if not more than, the amplification in the horizontal direction. Peak shear strain is found to be about 20% larger for near-field motions compared to far-field motions whereas maximum horizontal site amplification for far-field motions is found to be consistently larger than that of near-field motions, even though the differences between the two remain within the scatter resulting from individual ground motions.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Decision Science for Machine Learning (DeSciML)

The increasing use of machine learning (ML) models to support high-consequence decision making drives a need to increase the rigor of ML-based decision making. Critical problems ranging from climate change to nonproliferation monitoring rely on machine learning for aspects of their analyses. Likewise, future technologies, such as incorporation of data-driven methods into the stockpile surveillance and predictive failure analysis for weapons components, will all rely on decision-making that incorporates the output of machine learning models. In this project, our main focus was the development of decision scientific methods that combine uncertainty estimates for machine learning predictions, with a domain-specific model of error costs. Other focus areas include uncertainty measurement in ML predictions, designing decision rules using multiobjecive optimization, the value of uncertainty reduction, and decision-tailored uncertainty quantification for probability estimates. By laying foundations for rigorous decision making based on the predictions of machine learning models, these approaches are directly relevant to every national security mission that applies, or will apply, machine learning to data, most of which entail some decision context.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Tunable Multisite Proton-Coupled Electron Transfer Mediators: Distinct Pathways for Substrate Reduction Versus Competing Hydrogen Evolution

Proton-coupled electron transfer (PCET) reagents have emerged as powerful tools for transferring net H atoms to organic substrates from relatively weak X–H bonds. One advantage of employing PCET reagents is the tunability of the X–H bond strength by independently varying their redox potential and/or p K a for selective substrate reductions; however, the rational development of modular catalytic PCET reagents based on these features remains underdeveloped. In this work, we address important mechanistic questions relevant to a dimethylaniline-appended cobaltocene PCET mediator that our lab has previously introduced. Specifically, we examine where protonation occurs within the reactive Co(II, NH) + intermediate of a Brønsted-base modified cobaltocene mediator, whether substrate reduction and hydrogen evolution reaction (HER) proceed by a common or bifurcated mechanistic pathway, and how the redox, acid–base, and structural properties of PCET mediators can dictate their reactivity and selectivity. We show that substrate compatibility can be tuned and, via a model study with N -aryl imine substrates, provide data pointing to a multisite PCET (MS-PCET) pathway. Moreover, we rigorously characterize the site of protonation in the reactive reduced, protonated form of the mediator, and through kinetic analysis establish that the pathway for undesired competing HER is fundamentally different and involves Cp-ring protonation. Our findings point to a high degree of flexibility in the design of reductive PCET mediators.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

The Illumination of Thunderclouds by Lightning: 2. The Effect of GLM Instrument Threshold on Detection and Clustering

Abstract Lightning is measured from space using optical instruments that detect transient changes in the illumination of the cloud top. How much of the flash (if any) is recorded by the instrument depends on the instrument detection threshold. NOAA's Geostationary Lightning Mapper (GLM) employs a dynamic threshold that varies across the imaging array and changes over time. This causes flashes in certain regions and at night to be recorded in greater detail than other flashes, and threshold inconsistencies will impose biases on all levels of GLM data products. In this study, we quantify the impact of the varying GLM threshold on event/group/flash detection, flash clustering, and gridded product generation by imposing artificial thresholds on the event data taken from a thunderstorm with a low instrument threshold (∼0.7 fJ). We find that even modest increases in threshold severely impact event (60% loss by 2 fJ, 90% loss by 10 fJ) and group (25% loss by 2 fJ, 81% loss by 10 fJ) detection by suppressing faint illumination of the cloud top from weak sources and scattering. Flash detection is impacted less by threshold increases (4% loss by 2 fJ), but reductions are still significant at higher thresholds (35% loss by 10 fJ, or 44% if single‐group flashes are removed). Undetected pulses cause individual flashes to be split and severely impact the construction of gridded products. All of these factors complicate the interpretation of GLM data, particularly when trended over time under a changing threshold.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The cosmological evolution of self-interacting dark matter

We study the evolution of cosmological perturbations in dark-matter models with elastic and velocity-independent self interactions. Such interactions are imprinted in the matter-power spectrum as dark acoustic oscillations, which can be experimentally explored to determine the strength of the self scatterings. Models with self interactions have similarities to warm dark matter, as they lead to suppression of power on small scales when the dark-matter velocity dispersion is sizable. Nonetheless, both the physical origin and the extent of the suppression differ for self-interacting dark matter from conventional warm dark matter, with a dark sound horizon controlling the reduction of power in the former case, and a free-streaming length in the latter. We thoroughly analyze these differences by performing computations of the linear power spectrum using a newly developed Boltzmann code. We find that while current Lyman-α data disfavor conventional warm dark matter with a mass less than 5.3 keV, when self interactions are included at their maximal value consistent with bounds from the Bullet Cluster, the limits are relaxed to 4.4 keV. Lastly, we make use of our analysis to set novel bounds on light scalar singlet dark matter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

MACHINE LEARNING-ENABLED PREDICTION OF TRANSIENT INJECTION MAP IN AUTOMOTIVE INJECTORS WITH UNCERTAINTY QUANTIFICATION

Accurate prediction of injection profiles is a critical aspect of linking injector operation with engine performance and emissions. However, highly resolved injector simulations can take one to two weeks of wall-clock time, which is incompatible with engine design cycles with desired turnaround times of less than a day. Hence, it is important to reduce the time-to-solution of the internal flow simulations by several orders of magnitude to make it compatible with engine simulations. This work demonstrates a data-driven approach for tackling the computational overhead of injector simulations, whereby the transient injection profiles are emulated for a side-oriented, single-hole diesel injector using a Bayesian machine-learning framework. First, an interpretable Bayesian learning strategy was employed to understand the effect of design parameters on the total void fraction field. Then, autoencoders are utilized for efficient dimensionality reduction of the flowfields. Gaussian process models are finally used to predict the spatiotemporal void fraction field at the injector exit for unknown operating conditions. The Gaussian process models produce principled uncertainty estimates associated with the emulated flowfields, which provide the engine designer with valuable information of where the data-driven predictions can be trusted in the design space. The Bayesian flowfield predictions are compared with the corresponding predictions from a deep neural network, which has been transfer-learned from static needle simulations from a previous work by the authors. The emulation framework can predict the void fraction field at the exit of the orifice within a few seconds, thus achieving a speed-up factor of up to 38 x 10(6) over the traditional simulation-based approach of generating transient injection maps.

machine learning↗
DOE OSTI2026

From models to reality: a systematic review on simulated and measured residential heat pump energy savings

High-performance HVAC solutions are central to residential energy management. A substantial share of these are electric, reversible-cycle systems, with heat pumps representing the largest portion of current and near-term adoption. This review synthesizes peer-reviewed and grey literature on residential space heating and cooling heat pumps. The academic literature is dominated by modeling (73.8%), with limited field measurement (13.1%). Grey literature from United States serve as a supplemental resource providing measured savings. Conversions from electric-resistance heating consistently show the largest site energy reductions, while oil/propane baselines yield moderate savings, and gas baseline scenario often deliver small and region-dependent savings. This study cross-checks the grey literature measured data with simulation data filtered from the ResStock dataset. The comparison indicates a discrepancy between simulations and measured data: simulated site EUIs are typically lower than measured EUIs, but percentage energy savings fall in similar ranges, implying simulations capture directional effects while underestimating energy use. Factors associated with variability and model–measurement differences include system characterization and control representation (e.g., backup heat engagement, thermostat/setpoint strategies, commissioning/installation quality), occupant behavior, weather normalization, metering scope, and envelope characterization. This paper also outlines the proposed methodology for comparing simulation and measured data for heat pumps. It emphasizes the metrics used for comparison and units harmonization, building characteristics matching, and compact metadata are needed for simulations to match measured data. The proposed methodology is expected to improve the credibility of simulated savings as measured evidence grows.

Yu, Lili↗
DOE OSTI2021

Evaluation of hybrid evaporative-vapor compression air conditioners for different global climates

Currently, a majority of global residential air-conditioning requirements are met using cooling systems based on the vapor compression cycle (VCC). To meet the future demand for space cooling and to reduce the corresponding environmental impact, there is a need for alternative cooling systems which require less resources and exhibit a higher coefficient of performance (COP). One of proposed alternatives is called the hybrid evaporative-vapor compression (HEVC) cycle, which utilizes adiabatic latent cooling in combination with the VCC. In this paper, we conducted a feasibility analysis of a HEVC system by comparing its performance to that of VCC for various global climates. To accomplish this, we developed and validated models to simulate the performance of residential VCC and HEVC systems. ASHRAE weather data and design conditions were then used to compare the performance of the two systems. In general, HEVC systems are best suited for hot arid climates with energy reduction greater than 20%. Conversely, humid climates are not suitable for HEVC adoption due to degraded performance of evaporative coolers in these climates. In addition to comparing the energy savings from HEVC systems, it is also critical to analyze their water consumption. Generally, climates that benefit the most from HEVC technology tend to also experience water scarcity issues. Thus, both the energy savings and water consumption of HEVC systems must be analyzed to guide the discussion on their adoption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

China's plug-in hybrid electric vehicle transition: An operational carbon perspective

Assessing the emissions of plug-in hybrid electric vehicle (PHEV) operations is crucial for accelerating the carbon–neutral transition in the passenger car sector. This study is the first to adopt a bottom-up model to measure the real-world energy use and carbon dioxide emissions of China’s top twenty selling PHEV models across different regions from 2020 to 2022. The results indicate that (1) the actual electricity intensity of the best-selling PHEV models (20.2–38.2 kWh/100 km) was 30–40 % higher than the New European Driving Cycle values, and the actual gasoline intensity (4.7–23.5 L/100 km) was 3–6 times greater than the New European Driving Cycle values. (2) The overall energy use of the best-selling models varied among different regions, and the energy use from 2020 to 2022 in Southern China was double that Northern China and the Yangtze River Middle Reach. (3) The top-selling models emitted 4.7 megatons of carbon dioxide nationwide from 2020 to 2022, with 1.9 megatons released by electricity consumption and 2.8 megatons released by gasoline combustion. Furthermore, targeted policy implications for expediting the carbon–neutral transition within the passenger car sector are proposed. In essence, this study explores and compares benchmark data at both the national and regional levels, along with performance metrics associated with PHEV operations. The main objective is to aid nationwide decarbonization efforts, focusing on carbon reduction and promoting the rapid transition of road transportation toward a net-zero carbon future.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Pipe Parity Analysis of Seawater Desalination in the United States: Exploring Costs, Energy, and Reliability via Case Studies and Scenarios of Emerging Technology

As climate change-induced variables exacerbate water scarcities, the use of seawater reverse osmosis (SWRO) membrane desalination technology for treating seawater could potentially provide a long-term drought-proof source of drinking water. This study carried out a technoeconomic assessment (TEA) for three SWRO desalination plants in the U.S. and one in Israel to set baselines for the cost and energy consumption for seawater desalination. In addition, a breakeven curve for implementing SWRO desalination was estimated in relation to the cost of water conservation measures to meet drought-induced reduction of the traditional water supply. The results show that the cost of SWRO water production scales with the plant capacity while energy intensity is not dramatically different across the plants. The higher cost in some U.S. plants is due to high capital investment, including land acquisition and permitting. Variations in plant capacity utilization have the greatest impact on the levelized cost of water (LCOW) over the plant service life, suggesting the importance of reducing fouling and maintenance-related downtime. Scenario analysis of fixed labor cost reduction through process automation indicates investments in automation and sensing technology could result in long-term savings. Breakeven analysis shows the decision to adopt SWRO is highly dependent on the local cost associated with water conservation to meet water supply reduction. Moreover, a small reduction in SWRO cost can influence a shift toward the adoption of SWRO over water conservation measures. Incorporation of future water demand, water conservation potential, and water stress data around the nation indicates SWRO desalination could be an important contributor to the future municipal drinking water portfolio in the U.S.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Isolating Detrital and Diagenetic Signals in Magnetic Susceptibility Records From Methane‐Bearing Marine Sediments

Abstract Volume‐dependent magnetic susceptibility (κ) is commonly used for paleoenvironmental reconstructions in both terrestrial and marine sedimentary environments where it reflects a mixed signal between primary deposition and secondary diagenesis. In the marine environment, κ is strongly influenced by the abundance of ferrimagnetic minerals regulated by sediment transport processes. Post‐depositional alteration by H 2 S, however, can dissolve titanomagnetite, releasing reactive Fe that promotes pyritization and subsequently decreases κ. Here, we provide a new approach for isolating the detrital signal in κ and identifying intervals of diagenetic alteration of κ driven by organoclastic sulfate reduction (OSR) and the anaerobic oxidation of methane (AOM) in methane‐bearing marine sediments offshore India. Using the correlation of a heavy mineral proxy from X‐ray fluorescence data (Zr/Rb) and κ in unaltered sediments, we predict the primary detrital κ signal and identify intervals of decreased κ, which correspond to increased total sulfur content. Our approach is a rapid, high‐resolution method that can identify overprinted κ resulting from pyritization of titanomagnetite due to H 2 S production in marine sediments. In addition, total organic carbon, total sulfur, and authigenic carbonate δ 13 C measurements indicate that both OSR and AOM can drive the observed κ loss, but AOM drives the greatest decreases in κ. Overall, our approach can enhance paleoenvironmental reconstructions and provide insight into paleo‐positions of the sulfate‐methane transition zone, past enhancements of OSR or paleo‐methane seepage, and the role of detrital iron oxide minerals on the marine sediment sulfur sink, with consequences influencing the development of chemosynthetic biological communities at methane seeps.

58 GEOSCIENCES↗
DOE OSTI2024

Exploring CO 2 reduction and crossover in membrane electrode assemblies

Electrochemical CO 2 reduction (CO 2 R) using renewable electricity is a key pathway toward synthesizing fuels and chemicals. In this study, multi-physics modeling is used to interpret experimental data obtained for CO 2 R to CO using Ag catalysts in a membrane electrode assembly. The one-dimensional model is validated using measured CO 2 crossover and product formation rates. The kinetics of CO formation are described by Marcus–Hush–Chidsey kinetics, which enables accurate prediction of the experimental data by accounting for the reorganization of the solvent during CO 2 R. Further, the results show how the performance is dictated by competing phenomena including ion formation and transport, CO 2 solubility, and water management. The model shows that increasing the ion-exchange capacity of the membrane and surface area of the catalyst increases CO formation rates by >100 mA cm –2 without negatively impacting CO 2 utilization. Here we provide insights into how to manage the trade-off between productivity and CO 2 utilization in CO 2 electrolyzers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Simulation and characterization of cation disorder in ZnGeP 2

New optoelectronic materials are needed for improving the efficiency and reliability of devices such as solar cells. Cation ordering presents one means of controlling optoelectronic properties while introducing potential to also diversify the mineral constituents of electronic devices; however, the mechanisms of ordering are not yet well understood. To better understand cation ordering in a system integratable with current devices, we assess short- and long-range order parameters of ZnGeP 2 , a material closely lattice matched to Si. Structures are simulated using cluster-based Monte Carlo and first-principles calculations to compare structural distortions, periodicity, and local coordination environments in ZnGeP 2 to experimental data both from the literature and presented here. Comparing order parameters, we relate the transition in order parameters of ZnGeP 2 to that of ZnGeP 2 , discuss the reduction of band gaps with disorder, and show that traditional structural characterization alone is insufficient for understanding order in ZnGeP 2 .

14 SOLAR ENERGY↗
DOE OSTI2021

Aeroacoustic Assessment of Wind Plant Controls

The Aeroacoustic Assessment project aims to quantify changes in aeroacoustic noise generation by a utility scale wind turbine operating under imposed yaw offsets common for wake steering and wind plant control strategies. Active plant control utilizing wake deflection control strategies have been shown experimentally and computationally to reliably produce 1-2% of additional annual energy production (AEP) without significant changes in turbine structural loads, the potential impact on aeroacoustic emissions has yet to be quantified or completely understood. Yawed operation of a wind turbine changes the three-dimensional aerodynamic interaction between the rotor blades and the incoming atmospheric flow, leading to changes in noise generation. This work quantifies the extent to which active control induces additional aeroacoustic emissions from additional separation and other flow interaction dynamic effects. Given public concerns about wind turbine noise and the need for observational data required for regulators to establish noise restrictions, we must understand potential acoustic emissions resulting from active control prior to commercial deployment and the development of practical noise reduction methods and technologies. The work outlined in this report details the new aeroacoustic measurement capability developed at NREL and its application to making full-field observations of noise from a utility-scale wind turbine. Preliminary noise modeling with the aeroacoustics module in OpenFAST helped to establish the design of the experiment, specifically targeting the noise observed at observers distributed around the DOE-owned GE 1.5 MW wind turbine. Low-frequency and infrasound measurement capability implemented in this project establish an operational baseline for the wind turbine, setting the stage for future control, rotor blade, and turbine design research.

17 WIND ENERGY↗
DOE OSTI2024

Characterization of a Unique Pair of Ferredoxin and Ferredoxin NADP+ Reductase Isoforms That Operates in Non-Photosynthetic Glandular Trichomes

Our recent investigations indicated that isoforms of ferredoxin (Fd) and ferredoxin NADP+ reductase (FNR) play essential roles for the reductive steps of the 2C-methyl-D-erythritol 4-phosphate (MEP) pathway of terpenoid biosynthesis in peppermint glandular trichomes (GTs). Based on an analysis of several transcriptome data sets, we demonstrated the presence of transcripts for a leaf-type FNR (L-FNR), a leaf-type Fd (Fd I), a root-type FNR (R-FNR), and two root-type Fds (Fd II and Fd III) in several members of the mint family (Lamiaceae). The present study reports on the biochemical characterization of all Fd and FNR isoforms of peppermint (Mentha × piperita L.). The redox potentials of Fd and FNR isoforms were determined using photoreduction methods. Based on a diaphorase assay, peppermint R-FNR had a substantially higher specificity constant (kcat/Km) for NADPH than L-FNR. Similar results were obtained with ferricyanide as an electron acceptor. When assayed for NADPH–cytochrome c reductase activity, the specificity constant with the Fd II and Fd III isoforms (when compared to Fd I) was slightly higher for L-FNR and substantially higher for R-FNR. Based on real-time quantitative PCR assays with samples representing various peppermint organs and cell types, the Fd II gene was expressed very highly in metabolically active GTs (but also present at lower levels in roots), whereas Fd III was expressed at low levels in both roots and GTs. Our data provide evidence that high transcript levels of Fd II, and not differences in the biochemical properties of the encoded enzyme when compared to those of Fd III, are likely to support the formation of copious amounts of monoterpene via the MEP pathway in peppermint GTs. This work has laid the foundation for follow-up studies to further investigate the roles of a unique R-FNR–Fd II pair in non-photosynthetic GTs of the Lamiaceae.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Effect of Split-Injection Strategies on Engine Performance and Emissions under Cold-Start Operation

The recently concluded partnership for advancing combustion engines (PACE) was a US Department of Energy consortium involving multiple national laboratories focused on addressing key efficiency and emission barriers in light-duty engines. Generation of detailed experimental data and modeling capabilities to understand and predict cold-start behavior was a major pillar in this program. Cold-start, as defined by the time between first engine crank and three-way catalyst light-off, is responsible for a large percentage of NOx, unburned hydrocarbon, and particulate matter emissions in light-duty engines. Minimizing emissions during cold-start is a trade-off between achieving faster three-way catalyst light-off, and engine out emissions during that period. In this study, engine performance, emissions, and catalyst warmup potential were monitored while the engine was operated using a single direct injection (baseline case) as well as a two-way-equal-split direct injection strategy. These injection strategies were analyzed at a range of cold-start-operation relevant retarded spark timings of up to 25 degrees after top dead center of firing (dATDCf). A stoichiometric 2-bar NIMEP steady-state condition was used for all cases to simulate cold-start operation. Significant improvement in engine stability was observed with the two-way-split injection strategy at the retarded spark timings allowing for up to 2.5x increase in exhaust heat rate when engine operation is stability constrained. Similar fuel-loss-to-oil trends with exhaust heat rate were observed for both single and two-way-split injection strategies. However, the two-way split injection was observed to produce higher NOx emissions per unit exhaust heat rate. A single data point run with three-way-split direct injection at a very retarded spark-timing of 30 dATDCf pointed to further improvements in engine stability and reduction in fuel-loss-to-oil as compared to single injection strategy. Engine stability decreased as spark timing was initially retarded with a single injection but was observed to plateau and stabilize beyond spark timing of 10 dATDCf. Finally, for the two-way-split-injection strategy, retarding the start of injection (SOI) timing of the second injection led to a decrease in engine stability as well as an increase in soot emissions.

42 ENGINEERING↗
DOE OSTI2026

Advancing Building Performance: Field Results of Thin-Glass Triple-Pane Window Demonstrations

To meet California and the nation's ambitious energy targets, energy use in the building sector must drop dramatically. Windows continue to be the lowest thermally performing envelope system in the nation's buildings, resulting in poor overall envelope performance and potential impacts to human health and comfort. Current best practice new window performance is typically met by double-pane low-solar-gain glazing. Thin-glass triple-pane windows are a highly promising next step forward in performance and have been deployed in two California multi-family sites to quantify field performance and building energy savings. The technology assessed offers the performance benefits of traditional triple-pane but with little increase in weight or cost, enabling incremental costs competitive with alternative energy reduction solutions for the building envelope. This paper covers a detailed investigation into the demonstration project and measured performance benefits of the windows after a full year of data collection.

Hart, Robert↗
DOE OSTI2024

Multicriteria-Based Selection of Microalgae Biorefineries: Biomass Composition Defines the Most Suitable Product Portfolios

The supply of microalgae-derived biofuels and bioproducts will be vital in a global-scale bioeconomy. As the diversity of microalgae strains and their compositional plasticity may yield a wide array of products of market interest, the design of effective biorefineries is a central aspect in the path to making microalgae-based products available in the market. In this way, the conversion of microalgae biomass should be planned to employ mature technologies, while maximizing economic and environmental benefits obtained from a diverse product portfolio. This study applied sequential, hybrid Multicriteria Decision Analyses (MCDA) to aid the decision-making process of outlining the most suitable biorefining pathways for specific compositional profiles. For this, the methodology simultaneously considered multiple technical, economic, and environmental criteria, such as market aspects for the main algae-derived products, potential reduction in greenhouse gas (GHG) emissions provided by the biobased alternatives, and technology readiness level of conversion routes, among others. The framework was tested using productivity and compositional data for 13 high-productivity summer strains cultivated under varying nutrient availability. The analysis pointed to compositional profile being a key driver in defining the core biorefining strategy of algae biomass, with lipid-to-carbohydrate ratios higher than roughly 1 warranting the preferential processing of lipids into hydrocarbon fuels with the remainder of the algae biomass compounds being sent to higher-value applications, such as carboxylic acids and renewable thermoplastic substitutes. An in-depth process simulation, techno-economic assessment (TEA), and life-cycle analysis (LCA) effort was carried out as a closing step to corroborate the results stemming from the proposed framework. This study validates the use of MCDAs as a screening method prior to implementing more time-consuming analysis techniques and makes a compelling case for this approach as a product selection tool on a wide range of algae species, thus helping establish species-agnostic (but composition-driven) biorefineries.

biofuels↗