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At least 1,423 records · Page 79

Techno‐economic and greenhouse gas analyses of lignin valorization to eugenol and phenolic products in integrated ethanol biorefineries

Abstract This work presents techno‐economic and greenhouse gas (GHG) analyses of an ethanol biorefinery integrating lignin conversion into eugenol and other phenolics. Catalytic hydrogenolysis assisted by isopropanol (IPA) is used to convert the lignin recovered after ionic liquid (IL) pretreatment, saccharification, and fermentation. This process was compared to a biorefinery using lignin for energy generation and simulated in SuperPro Designer. Spatial analysis was performed to determine biorefinery locations and capacities in a Mexican state with potential for lignocellulosic biomass, including corn stover, sorghum stubble, and Jatropha fruit shells. Relative to the base case, diverting 50% of lignin to phenolics decreased the ethanol cost of production significantly due to the high market value of the co‐products. The minimum ethanol selling price (MESP) for this case was $2.02 gal −1 . The resulting cradle‐to‐gate GHG footprint of bioethanol was 21 g CO 2 ‐eq MJ −1 , a 78% reduction with respect to gasoline when system expansion is used for allocation. Using market value‐based allocation resulted in 82% GHG reduction. Analysis of scenarios showed that a biorefinery processing 3000 t day −1 biomass and diverting 80% of lignin to phenolics can potentially yield an MESP lower than $1.5 gal −1 . To achieve this, research should target a reduction in IL input by 30% and IPA input by 40%, together with more energy‐efficient separation processes. The reduction in IL and IPA can be achieved by decreasing their loading rates and increasing recycling. Sensitivity analysis showed that, for biomass prices higher than $45 t −1 , biorefinery capacities must exceed 5000 t d −1 biomass input. © 2019 Society of Chemical Industry and John Wiley & Sons, Ltd

Martinez‐Hernandez, Elias↗

ERTS-1 data applied to strip mining

Two coal basins within the western region of the Potomac River Basin contain the largest strip-mining operations in western Maryland and West Virginia. The disturbed strip-mine areas were delineated along with the surrounding geological and vegetation features by using ERTS-1 data in both analog and digital form. The two digital systems employed were (1) the ERTS analysis system, a point-by-point digital analysis of spectral signatures based on known spectral values and (2) the LARS automatic data processing system. These two systems aided in efforts to determine the extent and state of strip mining in this region. Aircraft data, ground-verification information, and geological field studies also aided in the application of ERTS-1 imagery to perform an integrated analysis that assessed the adverse effects of strip mining. The results indicated that ERTS can both monitor and map the extent of strip mining to determine immediately the acreage affected and to indicate where future reclamation and revegetation may be necessary.

Anderson, A. T.↗

Integrated Campaign Probabilistic Cost, Schedule, Performance, and Value for Program Office Support

This paper describes an integrated assessment tool developed at NASA Langley Research Center that incorporates probabilistic analysis of life cycle cost, schedule, launch performance, on-orbit performance, and value across a series of planned space-based missions, or campaign. Originally designed as an aid in planning the execution of missions to accomplish the National Research Council 2007 Earth Science Decadal Survey, it utilizes Monte Carlo simulation of a series of space missions for assessment of resource requirements and expected return on investment. Interactions between simulated missions are incorporated, such as competition for launch site manifest, to capture unexpected and non-linear system behaviors. A novel value model is utilized to provide an assessment of the probabilistic return on investment. A demonstration case is discussed to illustrate the tool utility.

Cornelius, David↗

Maximizing energy efficiency in wastewater treatment plants: A data-driven approach for waste heat recovery and an economic analysis using Organic Rankine Cycle and thermal energy storage

Maximizing energy efficiency through waste heat recovery (WHR) processes is crucial for sustainable and ecofriendly operations across multiple industries, notably in wastewater treatment plants (WWTPs). This work proposes a comprehensive approach for assessing the WHR feasibility in WWTPs, structured in two main objectives. Firstly, an Artificial Neural Network (ANN) model is developed to accurately predict WHR based on operational data, including biogas temperature, biogas pressure, daily production in kWh, and WHR values in kWh th . The second objective focuses on economically evaluating the WHR feasibility based on the estimated WHR values obtained by the ANN model, and then realistically assessing the economic feasibility of integrating the Organic Rankine Cycle (ORC) and Seasonal Thermal Energy Storage (STES) systems. With an application to the As-Samra WWTP located in Jordan, the developed ANN model demonstrates promising results in the validation phase, with a root mean square error (RMSE) of 2206 kWh/day, a mean absolute error (MAE) of 1674 kWh/day, and an R-squared (R 2 ) value of 68%. On the other hand, the economic analysis reveals that an optimal ORC system of 412.14 kW e capacity yields a Net Present Value (NPV) of 2.09 million US dollars, a Levelized Cost of Energy (LCOE) of 0.0749 USD/kWh, a Payback Period (PBP) of 4.8 years, and annual revenues of 428 kUSD. This work also investigates the techno-economic feasibility of integrating ORC-STES. Results indicate that the LCOE and PBP are highly affected by the ORC's capital cost, and integrating STES increases the LCOE to 0.0824 USD/kWh, rendering its integration with ORC infeasible. In conclusion, this study aims to advance the understanding and application of WHR in WWTPs, paving the way for more efficient and sustainable practices in the field.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Reliability Impacts in Life Support Architecture and Technology Selection

Equivalent System Mass (ESM) and reliability estimates were performed for different life support architectures based primarily on International Space Station (ISS) technologies. The analysis was applied to a hypothetical 1-year deep-space mission. High-level fault trees were initially developed relating loss of life support functionality to the Loss of Crew (LOC) top event. System reliability was then expressed as the complement (nonoccurrence) this event and was increased through the addition of redundancy and spares, which added to the ESM. The reliability analysis assumed constant failure rates and used current projected values of the Mean Time Between Failures (MTBF) from an ISS database where available. Results were obtained showing the dependence of ESM on system reliability for each architecture. Although the analysis employed numerous simplifications and many of the input parameters are considered to have high uncertainty, the results strongly suggest that achieving necessary reliabilities for deep-space missions will add substantially to the life support system mass. As a point of reference, the reliability for a single-string architecture using the most regenerative combination of ISS technologies without unscheduled replacement spares was estimated to be less than 1%. The results also demonstrate how adding technologies in a serial manner to increase system closure forces the reliability of other life support technologies to increase in order to meet the system reliability requirement. This increase in reliability results in increased mass for multiple technologies through the need for additional spares. Alternative parallel architecture approaches and approaches with the potential to do more with less are discussed. The tall poles in life support ESM are also reexamined in light of estimated reliability impacts.

Lange, Kevin E.↗

Flame acceleration and transition to detonation in a pre-/main-chamber combustion system

Numerical simulations are performed to study the mechanism of deflagration to detonation transition (DDT) in a pre-/main-chamber combustion system with a stoichiometric ethylene–oxygen mixture. A Godunov algorithm, fifth-order in space, and third-order in time, is used to solve the fully compressible Navier–Stokes equations on a dynamically adapting mesh. A single-step, calibrated chemical diffusive model described by Arrhenius kinetics is used for energy release and conservation between the fuel and the product. The two-dimensional simulation shows that a laminar flame grows in the pre-chamber and then develops into a jet flame as it passes through the orifice. A strong shock forms immediately ahead of the flame, reflecting off the walls and interacting with the flame front. The shock–flame interactions are crucial for the development of flame instabilities, which trigger the subsequent flame development. The DDT arises due to a shock-focusing mechanism, where multiple shocks collide at the flame front. A chemical explosive mode analysis (CEMA) criterion is developed to study the DDT ignition mode. Preliminary one-dimensional computations for a laminar propagating flame, a fast flame deflagration, and a Chapman–Jouguet detonation are conducted to demonstrate the validity of CEMA on the chemical-diffusive model, as well as to determine the proper conditioning value for CEMA diagnostic. The two-dimensional analysis with CEMA indicates that the DDT initiated by the shock-focusing mechanism can form a strong thermal expansion region at the flame front that features large positive eigenvalues for the chemical explosive mode and dominance of the local autoignition mode. Thus, the CEMA criterion proposed in this study provides a robust diagnostic for identifying autoignition-supported DDT, of which the emergence of excessive local autoignition mode is found to be a precursor. The effect of grid size, initial temperature, and orifice size are then evaluated, and results show that although the close-chamber DDT is highly stochastic, the detonation initiation mechanism remains robust.

42 ENGINEERING↗

Economic, Exergy, and Environmental Analyses of the Energy Assessments for U.S. Industries

Abstract This paper highlights the expected versus actual outcomes of 152 energy assessments that were performed between 2011 and 2020. The 1317 energy-assessment recommendations (ARs) are grouped into eight categories. This study adopted four measures per each category of recommendations: annual electricity savings, annual gas savings, annual cost savings, and annual CO2 emission reduction. The first part of the analysis compares the expected to the actually implemented values of the measures applied to each recommendation’s category. It was found that the percentages of the actual to the expected electricity, gas, and cost savings are 26.6%, 11.4%, and 17.1%, respectively, while the percentage of the actual to the expected CO2 reduction is 22%. Moreover, the second part of the analysis presents each category's implementation rate and the reasons for rejecting the unimplemented ARs. Cash flow and expensive initial investment resulted in rejecting 25% of ARs. Furthermore, the study proposes techniques and strategies to increase ARs’ implementation rate and improve private energy services companies’ implementation rate. Finally, exergy analysis is added to show the improvement that energy assessment achieves regarding exergy and exergy efficiencies of different industrial applications.

Energy & Fuels↗

H2@Scale: Technical and Economic Potential of Hydrogen as an Energy Intermediate

The H2@Scale concept is focused on developing hydrogen as an energy carrier and using hydrogen's properties to improve the national energy system. Specifically hydrogen has the abilities to (1) supply a clean energy source for industry and transportation and (2) increase the profitability of variable renewable electricity generators such as wind turbines and solar photovoltaic (PV) farms by providing value for otherwise potentially-curtailed electricity. Thus the concept also has the potential to reduce oil dependency by providing a low-carbon fuel for fuel cell electric vehicles (FCEVs), reduce emissions of carbon dioxide and pollutants such as NOx, and support domestic energy production, manufacturing, and U.S. economic competitiveness. The analysis reported here focuses on the potential market size and value proposition for the H2@Scale concept. It involves three analysis phases: 1. Initial phase estimating the technical potential for hydrogen markets and the resources required to meet them; 2. National-scale analysis of the economic potential for hydrogen and the interactions between willingness to pay by hydrogen users and the cost to produce hydrogen from various sources; and 3. In-depth analysis of spatial and economic issues impacting hydrogen production and utilization and the markets. Preliminary analysis of the technical potential indicates that the technical potential for hydrogen use is approximately 60 million metric tons (MMT) annually for light duty FCEVs, heavy duty vehicles, ammonia production, oil refining, biofuel hydrotreating, metals refining, and injection into the natural gas system. The technical potential of utility-scale PV and wind generation independently are much greater than that necessary to produce 60 MMT / year hydrogen. Uranium, natural gas, and coal reserves are each sufficient to produce 60 MMT / year hydrogen in addition to their current uses for decades to centuries. National estimates of the economic potential of hydrogen production using steam methane reforming of natural gas, high temperature electrolysis coupled with nuclear power plants, and low temperature electrolysis are reported. To generate the estimates, supply curves for those technologies are used. They are compared to demand curves that describe the market size for hydrogen uses and willingness to pay for that hydrogen. Scenarios are developed at prices where supply meets demand and are used to estimate energy use, emissions, and economic impacts.

13 HYDRO ENERGY↗

Potential Size of and Value Proposition for H2@Scale Concept

The H2@Scale concept is focused on developing hydrogen as an energy carrier and using hydrogen's properties to improve the national energy system. Specifically hydrogen has the abilities to (1) supply a clean energy source for industry and transportation and (2) increase the profitability of variable renewable electricity generators such as wind turbines and solar photovoltaic (PV) farms by providing value for otherwise potentially-curtailed electricity. Thus the concept also has the potential to reduce oil dependency by providing a low-carbon fuel for fuel cell electric vehicles (FCEVs), reduce emissions of carbon dioxide and pollutants such as NOx, and support domestic energy production, manufacturing, and U.S. economic competitiveness. The analysis reported here focuses on the potential market size and value proposition for the H2@Scale concept. It involves three analysis phases: 1. Initial phase estimating the technical potential for hydrogen markets and the resources required to meet them; 2. National-scale analysis of the economic potential for hydrogen and the interactions between willingness to pay by hydrogen users and the cost to produce hydrogen from various sources; and 3. In-depth analysis of spatial and economic issues impacting hydrogen production and utilization and the markets. Preliminary analysis of the technical potential indicates that the technical potential for hydrogen use is approximately 60 million metric tons (MMT) annually for light duty FCEVs, heavy duty vehicles, ammonia production, oil refining, biofuel hydrotreating, metals refining, and injection into the natural gas system. The technical potential of utility-scale PV and wind generation independently are much greater than that necessary to produce 60 MMT / year hydrogen. Uranium, natural gas, and coal reserves are each sufficient to produce 60 MMT / year hydrogen in addition to their current uses for decades to centuries. National estimates of the economic potential of hydrogen production using steam methane reforming of natural gas, high temperature electrolysis coupled with nuclear power plants, and low temperature electrolysis are reported. To generate the estimates, supply curves for those technologies are used. They are compared to demand curves that describe the market size for hydrogen uses and willingness to pay for that hydrogen. Scenarios are developed at prices where supply meets demand and are used to estimate energy use, emissions, and economic impacts.

13 HYDRO ENERGY↗

Method for rapid development of additive manufacturing parameter set

An apparatus includes a control system that defines a test part having multiple features of multiple feature types. The control system controls an additive manufacturing (AM) machine to print multiple copies of the test part, with each copy being printed according to a respective set of values used as printing parameters. A measurement system obtains a computed tomography (CT) image of each of the copies of the test part. An analysis system, for each of the plurality of feature types, analyzes the CT images to identify a selected set of values for the printing parameters. The analysis system identifies a portion of the CT image related to a first feature and assesses its density based on an average grayscale value. The AM machine is then controlled to print production parts according to, for each feature type of the production parts, the selected set of values for the printing parameters.

Bhattad, Pradeep↗

Validation of SE-EPI-based T2 mapping for characterization of prostate cancer: a new method compared with the traditional CPMG method

Purpose: We aim to compare the results of spin echo–echo planar imaging (SE-EPI)-based T2 mapping with those of the conventional Carr–Purcell–Meiboom–Gill (CPMG) method and to investigate the potential validity of SE-EPI-T2 mapping for the characterization of prostate cancer (PCa). Methods: Our retrospective study included 42 PCa patients and 42 noncancer patients who underwent 3.0T MRI with b values ranging from 0 to 2000 s/mm{sup 2} and echo times (TEs) ranging from 32 to 100 ms before biopsies. Bland–Altman analysis was used to compare the agreement between the two methods. The correlations between CPMG-T2 values and SE-EPI-T2 values at different b values were determined by Spearman’s rho analysis or Pearson analysis. The Mann–Whitney U test and two-sample t tests were used to analyze the differences between the cancerous and noncancerous groups. Results: Substantial agreement regarding the measurements was observed between the two methods. The average correlation between the CPMG-T2 values and SE-EPI-T2 values was moderate and positive, and the best correlations were found at b = 200 s/mm{sup 2} in the noncancer group (r = 0.557, P = 0.000) and at b = 100 s/mm{sup 2} in the cancer group (r = 0.537, P = 0.000). In addition, statistically significant differences were found between the noncancer and cancer groups in T2 values and ADC values (diff TEs) (P = 0.000). Conclusions: Substantial agreement in the measurements was found between the SE-EPI method and CPMG method. SE-EPI-based T2 mapping has potential clinical value for the prostate and can be considered an alternative to the traditional CPMG-T2 mapping method.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

My Virtual Cancer

Since each cancer has its own unique characteristics, each one can respond differently to the same treatments. Therefore, the creation of a digital twin (DT) of cancer can assist us in predicting the evolution of an individual's cancer through modeling each tumor's characteristics and response to treatment. Hence, we propose to take advantage of new advances in computational approaches and combine mechanistic, machine learning, and stochastic modeling approaches to create “My Virtual Cancer", a DT platform. To establish a personalized DT, we use patient-specific data for parameter estimations, sensitivity analysis, and uncertainty quantification. For each patient, we will estimate the values of parameters of their QSP model using the patient's data. We perform a multi-dimensional sensitivity analysis and uncertainty quantification on the mechanistic model to find a set of critical interactions and predict the intervals of confidence. Since this QSP model includes the data-driven mechanistic model of cells and molecules' interaction networks, one of the ultimate results of this DT would be the prediction of evolution of tumors.

60 APPLIED LIFE SCIENCES↗

Analysis of BOSS galaxy data with weighted skew-spectra

We present the first application of the weighted skew-spectra to analyze non-Gaussian information in galaxy survey data. Using the tree-level galaxy skew-spectra together with the one-loop power spectrum multipoles, we analyze the Sloan Digital Sky Survey (SDSS)-III Baryon Oscillation Spectroscopic Survey (BOSS) galaxy clustering data, and target our search towards the equilateral bispectrum shape of primordial non-Gaussianity. We use the Effective Field Theory model for the galaxy power spectrum and bispectrum, and account for systematic effects, such as the survey geometry. From our likelihood analysis, we find f NL equil = -34 +296 -334 at 68% CL, consistent with previous works, while systematic errors from our treatment of the survey geometry lead to an unreliable estimation of f NL ortho . As a result, we further constrain the bias and counterterm parameters, while keeping the cosmology fixed to Planck 2018 values. As a check, we also validate our analysis pipeline using theNseries simulation suite.

79 ASTRONOMY AND ASTROPHYSICS↗

Measurement of ocean wave heights using the Geos 3 altimeter

Radar altimeter signals transmitted from the low-orbiting satellite Geos 3 were analyzed for two selected orbits over high seas associated with hurricane 'Caroline' in the Gulf of Mexico and a North Atlantic storm. The measured values of significant wave height are in reasonable agreement with surface measurements, provided that the altimeter data are properly edited. The internal consistency of estimated wave heights for the North Atlantic storm, a standard deviation of 0.6 m or less, and the good agreement with surface truth lend credence to the method. A statistical analysis of the pulse slope variation gives estimated values of significant wave height within + or - 1 m of the true values 75% of the time for spatial averaging over 70 km.

Rufenach, C. L.↗

Geocentric gravitational constant determined from spacecraft radiometric data

The value of the geocentric gravitational constant was determined from the analysis of Doppler and range data during the near-earth phases of the trajectories of Mariners 9 and 10. Geocentric gravitational constant values (in units of cu km/sq s) for the two spacecraft were found to be: 398,600.7 plus or minus 0.2 for Mariner 9 and 398,600.6 plus or minus 0.2 for Mariner 10.

Esposito, P. B.↗

Composite laminate failure parameter optimization through four-point flexure experimentation and analysis

Fiber-reinforced composite materials offer light-weight solutions to many structural challenges. In the development of high-performance composite structures, a thorough understanding is required of the composite materials themselves as well as methods for the analysis and failure prediction of the relevant composite structures. However, the mechanical properties required for the complete constitutive definition of a composite material can be difficult to determine through experimentation. Therefore, efficient methods are necessary that can be used to determine which properties are relevant to the analysis of a specific structure and to establish a structure's response to a material parameter that can only be defined through estimation. The objectives of this paper deal with demonstrating the potential value of sensitivity and uncertainty quantification techniques during the failure analysis of loaded composite structures; and the proposed methods are applied to the simulation of the four-point flexural characterization of a carbon fiber composite material. Utilizing a recently implemented, phenomenological orthotropic material model that is capable of predicting progressive composite damage and failure, a sensitivity analysis is completed to establish which material parameters are truly relevant to a simulation's outcome. Then, a parameter study is completed to determine the effect of the relevant material properties' expected variations on the simulated four-point flexural behavior as well as to determine the value of an unknown material property. This process demonstrates the ability to formulate accurate predictions in the absence of a rigorous material characterization effort. Finally, the presented results indicate that a sensitivity analysis and parameter study can be used to streamline the material definition process as the described flexural characterization was used for model validation.

36 MATERIALS SCIENCE↗

Flowthrough Pretreatment of Softwood under Water-only and Alkali Conditions

Flowthrough pretreatment provides valuable insight in the fundamentals of deconstruction of plant biomass. In this study, the potential softwood degradation pathways under water-only and alkali conditions were determined by elucidating the deconstructed biomass-derived products at 0-270 °C for 2-10 min at a flow rate of 25 mL/min with water-only or alkaline at initial pH of 8, 9, 11, and 12, respectively. Results indicated that the initial pH value was a convenient indicator along with the severity parameter to control biomass degradation through the non-oxidative (pH<9) and oxidative (pH=9) pathways. Up to 100 % of hemi-sugars, 90 % of cellulose, and 70 % of lignin were derived from softwood under non-oxidative conditions at severity parameter LogR0 around 5.5, respectively. On the contrary, at pH 12, the oxidative degradation resulted in pretreated hydrolysate rich in monomeric and oligomeric phenolic products as well as glycolic acid, acetic acid, and formic acid from carbohydrates. The two dimensional 1H-13C heteronuclear single quantum coherence (HSQC) nuclear magnetic resonance (NMR) analysis revealed that non-oxidative degradation at initial pH values lower than 9 mainly cleaved ß-O-4, all of the ß-ß, and ß-5/a-O-4 linkages, whereas substantial aromatic ring structures with limited ß-O-4 structures remaining at pH 12 through oxidative degradation.

Zhang, Libing↗

Transcriptomic Network Analysis of Cyanobacterial-Methylotroph Interactions in Coculture and Axenic Conditions

A previous study demonstrated the potential for Cyanobacterial-Methylotroph cocultures to facilitate biogas processing as well as to be used in other biotechnological applications. To advance this technology, we investigated potential interactions between Cyanobacterium stanieri HL-69 (HL69) and Methylotuvimicrobium alkaliphilum 20Z (20Z) by inferring and analyzing gene co-expression networks under co-culture and axenic conditions. Five different co-expression networks were examined. These networks were inferred using gene expression profiles for 20Z axenic condition, HL-69 axenic, HL-69, 20Z coculture, HL-69 coculture, and cross-species HL-69-20Z coculture. Through the analysis of node (gene) betweenness and node normalized degree values in all five network cases, we compared adjustments in gene expression between growth conditions (axenic vs co-culture) as well as identify biological functions relevant to interspecies interactions. This analysis was done to distinguish between gene interactions within an organism and gene interactions between two organisms. Moreover, for all five cases we investigated two different network cutoff levels of 3,000 and 10,000. By shedding light on inter- and intra- species interactions, we hope to gain a better understanding of how these two organisms interact. This research will allow the investigation of further biotechnological applications of coculture systems and optimization of such applications for biotechnological purposes.

59 BASIC BIOLOGICAL SCIENCES↗