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At least 1,009 records · Page 56

Sun-view angle effects on reflectance factors of corn canopies

The effects of sun and view angles on reflectance factors of corn (Zea mays L.) canopies ranging from the six leaf stage to harvest maturity were studied on the Purdue University Agronomy Farm by a multiband radiometer. The two methods of acquiring spectral data, the truck system and the tower systrem, are described. The analysis of the spectral data is presented in three parts: solar angle effects on reflectance factors viewed at nadir; solar angle effects on reflectance factors viewed at a fixed sun angle; and both sun and view angles effect on reflectance factors. The analysis revealed that for nadir-viewed reflectance factors there is a strong solar angle dependence in all spectral bands for canopies with low leaf area index. Reflectance factors observed from the sun angle at different view azimuth angles showed that the position of the sensor relative to the sun is important in determining angular reflectance characteristics. For both sun and view angles, reflectance factors are maximized when the sensor view direction is towards the sun.

Ranson, K. J.↗

A Correction to the Stress–Strain Curve During Multistage Hot Deformation of 7150 Aluminum Alloy Using Instantaneous Friction Factors

Multistage stress–strain curve correction based on an instantaneous friction factor was studied for axisymmetric uniaxial hot compression of 7150 aluminum alloy. Experimental friction factors were calculated based on continuous isothermal axisymmetric uniaxial compression tests at various deformation parameters. Then, an instantaneous friction factor equation was fitted by mathematic analysis. After verification by comparing single-pass flow stress correction with traditional average friction factor correction, the instantaneous friction factor equation was applied to correct multistage stress–strain curves. The corrected results were reasonable and validated by multistage relative softening calculations. This research provides a broad potential for implementing axisymmetric uniaxial compression in multistage physical simulations and friction optimization in finite element analysis.

36 MATERIALS SCIENCE↗

Characterizing Seasonal Variation of the Atmospheric Mixing Layer Height Using Machine Learning Approaches

As machine learning becomes more integrated into atmospheric science, XGBoost has gained popularity for its ability to assess the relative contributions of influencing factors in the atmospheric boundary layer height. To examine how these factors vary across seasons, a seasonal analysis is necessary. However, dividing data by season reduces the sample size, which can affect result reliability and complicate factor comparisons. To address these challenges, this study replaces default parameters with grid search optimization and incorporates cross-validation to mitigate dataset limitations. Using XGBoost with four years of data from the atmospheric radiation measurement (ARM) (Southern Great Plains (SGP) C1 site, cross-validation stabilizes correlation coefficient fluctuations from 0.3 to within 0.1. With optimized parameters, the R value can reach 0.81. Analysis of the C1 site reveals that the relative importance of different factors changes across seasons. Lower tropospheric stability (LTS, ~0.53) is the dominant factor at C1 throughout the year. However, during DJF, latent heat flux (LHF, 0.44) surpasses LTS (0.22). In SON, LTS (0.58) becomes more influential than LHF (0.18). Further comparisons among the four long-term SGP sites (C1, E32, E37, and E39) show seasonal variations in relative importance. Notably, during JJA, the differences in the relative importance of the three factors across all sites are lower than in other seasons. This suggests that boundary layer development in the summer is not dominated by a single factor, reflecting a more intricate process likely influenced by seasonal conditions such as enhanced convective activity, higher temperatures, and humidity, which collectively contribute to a balanced distribution of parameter impacts. Furthermore, the relative importance of LTS gradually increases from morning to noon, indicating that LTS becomes more significant as the boundary layer approaches its maximum height. Consequently, the LTS in the early morning in autumn exhibits greater relative importance compared to other seasons. This reflects a faster development of the mixing layer height (MLH) in autumn, suggesting that it is easier to retrieve the MLH from the previous day during this period. The findings enhance understanding of boundary layer evolution and contribute to improved boundary layer parameterization.

54 ENVIRONMENTAL SCIENCES↗

Biodiesel production from engineered sugarcane lipids under uncertain feedstock compositions: Process design and techno-economic analysis

In this study, different process schemes were designed and evaluated for biodiesel production from engineered cane lipids with uncertain fatty acid compositions. Four different process schemes were compared under (i) thermal glycerolysis and (ii) enzymatic glycerolysis approaches. These schemes were based on the biodiesel yield and economic indicators such as the net present value (NPV) and the minimum selling price (MSP) of biodiesel. A scheme with polar lipid separation under thermal glycerolysis resulted in the maximum NPV ($\$96.5$ million) and minimum MSP ($\$1107$ /ton biodiesel), respectively. Through local sensitivity analysis, it was concluded that the cane lipid percentage is the most significant factor influencing process economics. A conjoint analysis of the lipid procurement price and cane lipid percent suggested that 15% cane lipids with a low lipid procurement price ($\$0.536$ /kg) results in a positive NPV. When the cane lipid price is higher (> $\$0.80$ /kg), a 20% lipid content should be considered to achieve a positive NPV. At 20% cane lipids, the worst-case and best-case scenarios were evaluated by analyzing the interplay of the three most important parameters, Here, the best-case scenario revealed that the minimum NPV under any process scheme could yield more than $\$100$ million (or MSP: $\$0.80$ /L), and the worst-case analysis showed that losses incurred by the plant could be as high as 80 million (MSP: $\$1.36$ /L). A Monte Carlo simulation indicated that there is a 70% chance of the plant being profitable (NPV > 0).

09 BIOMASS FUELS↗

Data from Biodiesel Production from Engineered Sugarcane Lipids under Uncertain Feedstock Compositions: Process Design and Techno-Economic Analysis

In this study, different process schemes were designed and evaluated for biodiesel production from engineered cane lipids with uncertain fatty acid compositions. Four different process schemes were compared under (i) thermal glycerolysis and (ii) enzymatic glycerolysis approaches. These schemes were based on the biodiesel yield and economic indicators such as the net present value (NPV) and the minimum selling price (MSP) of biodiesel. A scheme with polar lipid separation under thermal glycerolysis resulted in the maximum NPV ($96.5 million) and minimum MSP ($1107/ton biodiesel), respectively. Through local sensitivity analysis, it was concluded that the cane lipid percentage is the most significant factor influencing process economics. A conjoint analysis of the lipid procurement price and cane lipid percent suggested that 15% cane lipids with a low lipid procurement price ($0.536/kg) results in a positive NPV. When the cane lipid price is higher (>$0.80/kg), a 20% lipid content should be considered to achieve a positive NPV. At 20% cane lipids, the worst-case and best-case scenarios were evaluated by analyzing the interplay of the three most important parameters, The best-case scenario revealed that the minimum NPV under any process scheme could yield more than $100 million (or MSP: $0.80/L), and the worst-case analysis showed that losses incurred by the plant could be as high as $80 million (MSP: $1.36/L). A Monte Carlo simulation indicated that there is a 70% chance of the plant being profitable (NPV > 0).

Conversion↗

Introduction to the Bioproduct Transition Dynamics Model

The U.S. Department of Energy, Bioenergy Technologies Office has a broad understanding of different conversion processes that produce bioproducts (chemicals derived from biomass feedstocks) and the market attributes of those processes. However, bioproducts have in many cases proven to be difficult to scale up to commercial production and bring to market, and there is currently a need for greater understanding around the possible successful scenarios for advancing the bioproducts industry. Insight into the myriad factors that impact the success of individual bioproducts and the growth of the bioproducts industry will enable bioproduct stakeholders to evaluate strategies for development and investment that could achieve the greatest impact. An understanding of these factors will also enable the identification of synergies between the bioproducts and biofuels industries that occur through shared learning and co-production. The Bioproduct Transition Dynamics (BTD) model explores questions such as the following: what are the factors that separate a successful, commercially produced bioproduct like succinic acid from one that never progresses beyond bench-scale lab research? Can these factors be influenced by stakeholders, and to what extent? The BTD model uses system dynamics to capture the impacts of investor decision-making, bioproduct techno-economics, and market factors during the early stages of bioproduct development. Key components of the BTD model include techno-economic benchmarks that inform the investor decision-making process, failures and setbacks in development and the resulting need for additional work, and the impacts of effective or ineffective management during each development stage. These factors and their interactions are tracked through bench-scale laboratory research, piloting, demoing, and the construction and operation of the first commercial-scale plant. Bioproduct development is linked to the biofuels industry through a shared-learning model, enabling the benefit to biofuels from bioproduct technology and feedstock supply chain development to be quantified. A wide variety of bioproducts can be analyzed using the BTD model, including bioproducts that have been developed through economic or policy-driven mechanisms, and those with either niche (low volume) or scalable (high volume) markets. The BTD model also has the potential to apply to technology development processes outside the bioproducts industry; background research performed for this project has shown that the early stages of technology development are similar, and impacted by similar factors, regardless of the exact industry. This presentation will cover the BTD model logic, input data, validation process, and results of a sensitivity analysis based on techno-economic data for succinic acid. The sensitivity analysis was performed to identify factors with the largest impact on the eventual success or failure of a bioproduct. Results indicate that management effectiveness, which affects how efficiently money spent is converted into technological advancements, is the single most important factor in determining whether a bioproduct reaches commercial-scale production. The capacity of the first commercial plant and the type of biomass feedstock used, as well as the presence of government support in the form of cost-sharing, were also identified as significant factors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A System Dynamics Model of Early-Stage Transition Dynamics in the Bioproducts Industry

The U.S. Department of Energy, Bioenergy Technologies Office has a broad understanding of different conversion processes that produce bioproducts (chemicals derived from biomass feedstocks) and the techno-economic attributes of those processes. However, bioproducts have in many cases proven to be difficult to scale up to commercial production, and there is currently a need for greater understanding around the possible successful scenarios for advancing the bioproducts industry. Insight into the myriad factors that impact the success of individual bioproducts and the growth of the bioproducts industry will enable bioproduct stakeholders to evaluate strategies for development and investment that could achieve the greatest impact. An understanding of these factors will also enable the identification of synergies between the bioproducts and biofuels industries that occur through shared learning and co-production. The Bioproduct Transition Dynamics (BTD) model explores questions such as the following: what are the factors that separate a successful, commercially produced bioproduct like succinic acid from one that never progresses beyond bench-scale lab research? Can these factors be influenced by stakeholders, and to what extent? The BTD model uses system dynamics to capture the impacts of investor decision-making, bioproduct techno-economics, and end use factors during the early stages of bioproduct development. Key components of the BTD model include techno-economic benchmarks that inform the investor decision-making process, failures and setbacks in development and the resulting need for additional work, and the impacts of effective or ineffective management during each development stage. These factors and their interactions are tracked through bench-scale laboratory research, piloting, demoing, and the construction and operation of the first commercial-scale plant. Bioproduct development is linked to the biofuels industry through a shared-learning model, enabling the benefit to biofuels from bioproduct technology and feedstock supply chain development to be quantified. A wide variety of bioproducts can be analyzed using the BTD model, including bioproducts that have been developed through economic or policy-driven mechanisms, and those with either niche (low volume) or scalable (high volume) demand. The BTD model also has the potential to apply to technology development processes outside the bioproducts industry; background research performed for this project has shown that the early stages of technology development are similar, and impacted by similar factors, regardless of the exact industry. This presentation will cover the BTD model logic, input data, validation process, and results of a sensitivity analysis based on techno-economic data for succinic acid. The sensitivity analysis was performed to identify factors with the largest impact on the eventual success or failure of a bioproduct. Results indicate that management effectiveness, which affects how efficiently money spent is converted into technological advancements, is the single most important factor in determining whether a bioproduct reaches commercial-scale production. The capacity of the first commercial plant and the type of biomass feedstock used, as well as the presence of government support in the form of cost-sharing, were also identified as significant factors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Risk-Based Causal Modeling of Airborne Loss of Separation

Maintaining safe separation between aircraft remains one of the key aviation challenges as the Next Generation Air Transportation System (NextGen) emerges. The goals of the NextGen are to increase capacity and reduce flight delays to meet the aviation demand growth through the 2025 time frame while maintaining safety and efficiency. The envisioned NextGen is expected to enable high air traffic density, diverse fleet operations in the airspace, and a decrease in separation distance. All of these factors contribute to the potential for Loss of Separation (LOS) between aircraft. LOS is a precursor to a potential mid-air collision (MAC). The NASA Airspace Operations and Safety Program (AOSP) is committed to developing aircraft separation assurance concepts and technologies to mitigate LOS instances, therefore, preventing MAC. This paper focuses on the analysis of causal and contributing factors of LOS accidents and incidents leading to MAC occurrences. Mid-air collisions among large commercial aircraft are rare in the past decade, therefore, the LOS instances in this study are for general aviation using visual flight rules in the years 2000-2010. The study includes the investigation of causal paths leading to LOS, and the development of the Airborne Loss of Separation Analysis Model (ALOSAM) using Bayesian Belief Networks (BBN) to capture the multi-dependent relations of causal factors. The ALOSAM is currently a qualitative model, although further development could lead to a quantitative model. ALOSAM could then be used to perform impact analysis of concepts and technologies in the AOSP portfolio on the reduction of LOS risk.

Geuther, Steven C.↗

Evaluation and Analysis of the ANSI X3T9.5 (FDDI) PMD and Proposed SMF-PMD as Influenced by Various Fiber Link Characteristics

The purpose of this project is to evaluate the operational parameters of the Kennedy Space Center (KSC) fiber optic cable plant. The evaluation is based on the Fiber Distributed Data Interface (FDDI) Physical Medium Dependent (PMD) and Single Mode Fiber (SMF) PMD standards. From the KSC fiber profile, it would be necessary to develop the modifications needed in existing FDDI PMD and proposed SMF-PMD standards to provide for FDDI implementation and operation at KSC. This analysis should examine the major factors that influence the operating conditions of the KSC fiber plant. These factors would include, but are not limited to the number and type of connectors, attenuation and dispersion characteristics of the fiber, non-standard fiber sizes, modal bandwidth, and many other relevant or significant fiber plant characteristics that effect FDDI characteristics. This analysis is needed to gain a better understanding of overall impact that each of these factors have on FDDI performance at KSC.

Wernicki, M. Chris↗

Design and evaluation of FDDI fiber optics networkfor Ethernets, VAX's and Ingraph work stations

The purpose of this project is to design and evaluate the FDDI Fiber Optics Network for Ethernets, VAX's, and Ingraph work stations. From the KSC Headquarters communication requirement, it would be necessary to develop the FDDI network based on IEEE Standards outlined in the ANSI X3T9.5, Standard 802.3 and 802.5 topology - direct link via intermediate concentrator and bridge/router access. This analysis should examine the major factors that influence the operating conditions of the Headquarters Fiber plant. These factors would include, but are not limited to the interconnecting devices such as repeaters, bridges, routers and many other relevant or significant FDDI characteristics. This analysis is needed to gain a better understanding of overall FDDI performance.

Wernicki, M. Chris↗

Simulation and Correction of Triana-Viewed Earth Radiation Budget with ERBE/ISCCP Data

This paper describes the simulation of the earth radiation budget (ERB) as viewed by Triana and the development of correction models for converting Trianaviewed radiances into a complete ERB. A full range of Triana views and global radiation fields are simulated using a combination of datasets from ERBE (Earth Radiation Budget Experiment) and ISCCP (International Satellite Cloud Climatology Project) and analyzed with a set of empirical correction factors specific to the Triana views. The results show that the accuracy of global correction factors to estimate ERB from Triana radiances is a function of the Triana position relative to the Lagrange-1 (L1) or the Sun location. Spectral analysis of the global correction factor indicates that both shortwave (SW; 0.2 - 5.0 microns) and longwave (LW; 5 -50 microns) parameters undergo seasonal and diurnal cycles that dominate the periodic fluctuations. The diurnal cycle, especially its amplitude, is also strongly dependent on the seasonal cycle. Based on these results, models are developed to correct the radiances for unviewed areas and anisotropic emission and reflection. A preliminary assessment indicates that these correction models can be applied to Triana radiances to produce the most accurate global ERB to date.

Huang, Jian-Ping↗

Buckling Test and Analysis of the 8-foot-diameter Sandwich Composite Cylinder Test Article CTA8.3 as Part of the Shell Buckling Knockdown Factor Project: Test Dates 16~19 December 2019

This report describes work that is part of SBKF-the test and analysis results from the third SBKF cylindrical sandwich composite test article, which was designated SBKF-P3-CYL-CTA8.3. This test was the third in a series of tests on sandwich composite cylinders that can be used to experimentally validate analysis methods, which in turn can be used to develop analysis-based shell buckling design guidelines for sandwich composite launch-vehicle cylindrical structures. The primary objectives of this test were to interrogate the structural capability of the composite test article, and to verify the test-article design and analysis approach for cylinders subjected to axial compression and combined compression and bending loads.

Sandwich composite cylinder↗

Investigation of Fundamental Modeling and Thermal Performance Issues for a Metallic Thermal Protection System Design

A study was performed to develop an understanding of the key factors that govern the performance of metallic thermal protection systems for reusable launch vehicles. A current advanced metallic thermal protection system (TPS) concept was systematically analyzed to discover the most important factors governing the thermal performance of metallic TPS. A large number of relevant factors that influence the thermal analysis and thermal performance of metallic TPS were identified and quantified. Detailed finite element models were developed for predicting the thermal performance of design variations of the advanced metallic TPS concept mounted on a simple, unstiffened structure. The computational models were also used, in an automated iterative procedure, for sizing the metallic TPS to maintain the structure below a specified temperature limit. A statistical sensitivity analysis method, based on orthogonal matrix techniques used in robust design, was used to quantify and rank the relative importance of the various modeling and design factors considered in this study. Results of the study indicate that radiation, even in small gaps between panels, can reduce significantly the thermal performance of metallic TPS, so that gaps should be eliminated by design if possible. Thermal performance was also shown to be sensitive to several analytical assumptions that should be chosen carefully. One of the factors that was found to have the greatest effect on thermal performance is the heat capacity of the underlying structure. Therefore the structure and TPS should be designed concurrently.

Blosser, Max L.↗

Extraction and Parametrization of Isobaric Trinucleon Elastic Cross Sections and Form Factors

By mining data from Jefferson Lab Hall A experiment E08-014 a new 3 He elastic cross section was extracted from a large quasielastic background. This measurement was taken with an initial beam energy of 3.356 GeV and an angle of 20.51°. The cross section was found to be 1.345 × 10 -6 µb/sr ± 0.086 × 10 -6 µb/sr at Q 2 = 34.19 fm -2 . This new data point falls approximately halfway between the first and second diffractive minima of the 3 He form factors. When combined with recent high Q 2 3 He elastic cross section measurements from Jefferson Lab and MIT-Bates this new data point improves our knowledge of the cross section and form factors at large momentum transfers. The new high Q 2 data motivate a reanalysis of the 3 He elastic cross section world data and provide an improved understanding of the magnetic form factor in particular. For this analysis the elastic cross section world data for 3 He, and its mirror nuclei 3 H, were collected. The world data spans a time frame from 1965 to 2016. The dataset contains electron energy ranges from tens of MeV to above 12 GeV for measurements performed at many different facilities. The world data were then fit using a sum of Gaussians parametrization which allowed for the extraction of both targets’ magnetic and electric form factors which were then used to calculate charge densities and radii. The new charge and magnetic form factors for 3 H and the charge form factor for 3 He are in good agreement with the 1994 fits from Amroun et al . However, the addition of the new high Q 2 data has caused the 3 He magnetic form factor’s first diffractive minimum to shift up in Q 2 by 1-3 fm -2 while also decreasing the magnitude of the magnetic form factor above Q2 ≈ 20 fm -2 . The first diffractive minima for 3H are located at Q2 ≈ 13 fm -2 and Q 2 ≈ 23-24 fm -2 for the charge and magnetic form factors respectively. The first diffractive minima for 3 He are located at Q 2 ≈ 11 fm -2 and Q 2 ≈ 17-20 fm -2 for the charge and magnetic form factors respectively. The charge radius for 3 He was found to be 1.90 fm ± 0.00144 fm in reasonable agreement with past measurements, and the charge radius for 3 H was found to be 2.02 fm ± 0.0133 fm which is much larger than past measurements. However, each of these charge radii has an additional uncertainty that must be applied to them due to allowing all parameters to float freely during the sum of Gaussians fitting procedure. This additional uncertainty should be small for 3 He, but it is likely quite significant for 3 H and would help bring this charge radius closer to agreement with past measurements that made different fitting choices. Unfortunately, this analysis was unable to quantify this additional uncertainty. The new form factor fits were compared to modern theoretical predictions from the 2016 paper of Marcucci et al . The ‘conventional’ theoretical approach applied in this paper modelled two and three-body nucleon interactions with relativistic corrections and was reasonably successful at predicting the charge form factors of 3 H and 3 He. χEFT predictions were also often successful. However, while the ‘conventional’ approach still performed best, theory failed to accurately predict the magnetic form factors of either 3 H or 3 He. The first diffractive minimum of the new 3 He magnetic form factor fits actually moved further away from theory. This disagreement between theory and experiment provides motivation for new asymmetry measurements using polarized 3 He and a polarized electron beam. When the beam is scanned in Q 2 on the target the sign of the asymmetry will flip at the form factor minima pinning down their true location.

Barcus, Scott↗

Frequency domain measurements of melt pool recoil force using modal analysis

Recoil pressure is a critical factor affecting the melt pool dynamics during Laser Powder Bed Fusion (LPBF) processes. Recoil pressure depresses the melt pool. When the recoil pressure is low, thermal conduction and capillary forces may be inadequate to provide proper fusion between layers. However, excessive recoil pressure can produce a keyhole inside the melt pool, which is associated with gas porosity. Direct recoil pressure measurements are challenging because it is localized over an area proportionate to the laser spot size producing a force in the mN range. This paper reports a vibrationbased approach to quantify the recoil force exerted on a part in a commercial LPBF machine. The measured recoil force is consistent with estimates from high speed synchrotron imaging of entrained particles, and the results show that the recoil force scales with applied laser power and is inversely related to the laser scan speed. These results facilitate further studies of melt pool dynamics and have the potential to aid process development for new materials.

42 ENGINEERING↗

Engineering support for magnetohydrodynamic power plant analysis and design studies

The major factors which influence the economic engineering selection of stack inlet temperatures in combined cycle MHD powerplants are identified and the range of suitable stack inlet temperatures under typical operating conditions is indicated. Engineering data and cost estimates are provided for four separately fired high temperature air heater (HTAH) system designs for HTAH system thermal capacity levels of 100, 250, 500 and 1000 MWt. An engineering survey of coal drying and pulverizing equipment for MHD powerplant application is presented as well as capital and operating cost estimates for varying degrees of coal pulverization.

Carlson, A. W.↗

Element-by-element Solution Procedures for Nonlinear Structural Analysis

Element-by-element approximate factorization procedures are proposed for solving the large finite element equation systems which arise in nonlinear structural mechanics. Architectural and data base advantages of the present algorithms over traditional direct elimination schemes are noted. Results of calculations suggest considerable potential for the methods described.

Hughes, T. J. R.↗