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DOE OSTI2018

Valuing catastrophe bonds involving correlation and CIR interest rate model

Natural catastrophes lead to problems of insurance and reinsurance industry. Classic insurance mechanisms are often inadequate for dealing with consequences of catastrophic events. Therefore, new financial instruments, including catastrophe bonds (cat bonds), were developed. In this paper we price the catastrophe bonds with a generalized payoff structure, assuming that the bondholder’s payoff depends on an underlying asset driven by a stochastic jump-diffusion process. Simultaneously, the risk-free spot interest rate has also a stochastic form and is described by the multi-factor Cox–Ingersoll–Ross model. We assume the possibility of correlation between the Brownian part of the underlying asset and the components of the interest rate model. Using stochastic methods, we prove the valuation formula, which can be applied to the cat bonds with various payoff functions. We use adaptive Monte Carlo simulations to analyze the numerical properties of the obtained pricing formula for various settings, including some similar to the practical cases.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

On the convergence and convergence order of finite volume gradient schemes for oblique derivative boundary value problems

This work is an improvement of the previous note (Bradji in: Fuhrmann et al., Finite volumes for complex applications VII–methods, theoretical aspects. Proceedings of the FVCA 7, Berlin, 2014) which dealt with the convergence analysis of a finite volume scheme for the Poisson’s equation with a linear oblique derivative boundary condition. The formulation of the finite volume scheme given in Bradji (in: Fuhrmann et al., Finite volumes for complex applications VII–methods, theoretical aspects. Proceedings of the FVCA 7, Berlin, 2014) involves the discrete gradient introduced recently in Eymard et al. (IMA J Numer Anal 30(4):1009–1043, 2010). In this paper, we consider the convergence analysis of finite volume schemes involving the discrete gradient of Eymard et al. (IMA J Numer Anal 30(4):1009–1043, 2010) for elliptic and parabolic equations with linear oblique derivative boundary conditions. Linear oblique derivative boundary conditions arise for instance in the study of the motion of water in a canal, cf. Lesnic (Commun Numer Methods Eng 23(12):1071–1080, 2007). We derive error estimates in several norms which allow us to get error estimates for the approximations of the exact solutions and its first derivatives. In particular, we provide an error estimate between the gradient of the exact solutions and the discrete gradient of the approximate solutions. Convergence of the family of finite volume approximate solutions towards the exact solution under weak regularity assumption is also investigated. In the case of parabolic equations with oblique derivative boundary conditions, we develop a new discrete a priori estimate result. The proof of this result is based on the use of a discrete mean Poincaré–Wirtinger inequality. Thanks to the stated a priori estimate and to a comparison with an appropriately chosen auxiliary finite volume scheme, we derive the convergence results. This work can be viewed as a continuation of the previous work (Bradji and Gallouët in Int J Finite Vol 3(2):1–35, 2006) where a convergence analysis for a finite volume scheme, based on the admissible mesh of Eymard et al. (In: Ciarlet and Lions, Handbook of numerical analysis, North-Holland, Amsterdam, 2000), for the Poisson’s equation with a linear oblique derivative boundary conditions is given. The obtained convergence results do not require any relation between the mesh sizes of the spatial and time discretizations. Some numerical tests are presented for both elliptic and parabolic equations. In particular, we present three methods to compute the discrete solution.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Extended Newton-type method for nonlinear functions with values in a cone

In this paper, we consider the problem of finding solutions of nonlinear inclusion problems in Banach space. Using convex optimization techniques introduced by Robinson (Numer Math 19:341–347, 1972), a convergence theorem for Kantorovich-like methods is given, which improves the results of Yamamoto (Jpn J Appl Math 3(2):295–313, 1986; Numer Math 51(5):545–557, 1987) and Robinson (Numer Math 19:341–347, 1972). The result is compared with previously known results. Numerical examples further justify the theoretical results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Gender Equity and Mainstreaming in Renewable Energy Policies - Empowering Women in the Energy Value Chain in the Economic Community of West African States (ECOWAS)

Using practice theories as the analytical framework, this paper assesses the potential of the Economic Community of West African States' (ECOWAS) first ever regional policy on Gender Mainstreaming in Energy Access to produce the desired behavioral changes envisioned. The policy came to fruition after a multi-year, multi-stakeholder effort of research, advocacy, and consensus building; all spearheaded by an institution of the community, the ECOWAS Centre for Renewable Energy and Energy Efficiency (ECREEE). The success of the ECOWAS policy has led to the development of a related regional level legal instrument, monitoring protocols, institutional evolutions, as well as replication efforts in other African regions. The policy's provisions were aimed at changing the mind-sets and, eventually, behaviors of people concerned and were designed in order to increase its chances of successful implementation; however, the onus lies on the constituent governments of the community to provide incentives for its full and effective implementation in order to guarantee its success.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Explainable machine learning to quantify the value of proximal remote sensing in latent energy flux estimation

Proximal remote sensing has the potential to provide critical information on vegetation biophysical factors that can predict land-atmosphere exchange of water and energy. Latent energy (LE) flux is traditionally estimated using process-based models which rely on vegetation parameters that change during the growing season. Data-driven models have the potential to address these issues by offering flexible predictor selection and more efficient utilization of the information in predictor sets. These models require careful choice of predictors to avoid redundancy and allow robust cross-validation. In this study we present a systematic and comprehensive evaluation of machine learning (ML) models to assess the capability of meteorological and proximal sensing data for predicting LE at a half-hourly temporal resolution across multiple growing seasons for an agricultural system. The results presented here demonstrate that a model using four environmental predictors in combination with two proximal sensing variables can capture 88 % of the variability in LE. ML models using only three predictors (one meteorological and two proximal remote sensing) captured 81 % of LE variability, offering the best trade-off between performance and complexity. An ML model utilizing only two predictors, one proximal remote sensing variable and downwelling radiation, captured 77 % of LE variability. These results demonstrate the power of proximal remote sensing and meteorological observations to estimate land-atmosphere water vapor exchange, providing a solution where more direct methods such as eddy covariance are not available and for evaluations of agronomic management and genotypic variations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Low temperature catalytic conversion of CH 4 , CO 2 , and C 2 H 4 to value-added C 3 oxygenates and olefins via C 1 -C 2 coupling on Pd-Au/CeO 2

The catalytic conversion of CH 4 and CO 2 in the presence of more reactive co-reactants C 2 H 4 and O 2 on Pd-Au/CeO 2 is achieved at 200 °C and elevated pressures. Propene and acetone were produced from the catalyzed reaction of CH 4 +C 2 H 4 +O 2 ; addition of CO 2 to the reactant stream produced methyl acetate (MAc) but it significantly reduced the C-selectivities of propene and acetone. DRIFTS experiments confirmed the formation of methoxy species from CH 4 +CO 2 at 200 °C, which is an intermediate in the formation of MAc. Here, control experiments with blanks, and with CeO 2 did not show any propene, acetone, or MAc products. The complete oxidation of C 2 H 4 was avoided; the catalyst is stable, and reactant conversions and product yields were sustained for the observed 1200 min time-on-stream, indicating that there is little or no carbon deposition and sintering. This direct coupling of CH 4 and C 2 H 4 intermediates to higher carbon-number products at 200 °C is significant.

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

Creating values from wastes: Producing biofuels from waste cooking oil via a tandem vapor-phase hydrotreating process

Here, this study is focused on producing biofuels from waste oils via a tandem vapor-phase hydrotreating process in a pressurized two-stage fixed bed reactor over a bifunctional Ni/Al 2 O 3 -SiO 2 catalyst under 0.25 MPa H 2 . A 100% hydrodeoxygenation efficiency both in liquid and gas products was observed, yielding 83.9 wt% C 5 -C 19 n-alkanes which corresponds to a 7.4-fold increase compared with that obtained from non-catalytic conversion. The hydrodeoxygenation mechanism of waste cooking oil in the catalytic tandem hydrotreating process induced by Ni/Al 2 O 3 -SiO 2 was proposed. The hydropyrolysis temperature in the first reactor, hydrogenation temperature in the second reactor, reaction pressure, catalyst to waste cooking oil mass ratio, and gas hourly space velocity (GHSV) was optimized at 550 °C, 300 °C, 0.25 MPa, 3, and 56 s -1 , respectively. The application potential of this cascade vapor-phase hydrotreating process was evaluated by employing different waste oils such as palm kernel oil, woody oil (swida wilsoniana), soapstock, and waste lubricating oil as feedstock, giving C 5 to C 19 n-alkane yields ranging from 21.6 to 87.5 wt%. This work provides a novel and promising approach to upcycle waste oils into upgraded biofuels compared with conventional catalytic pyrolysis.

09 BIOMASS FUELS↗
DOE OSTI2024

The value of adding black carbon to community monitoring of particulate matter

Low-cost particulate matter (PM) sensors are increasingly used by researchers, public health agencies, and the public to measure spatial and temporal variations in air pollution, which can inform strategies for community air pollution reduction. While low-cost PM sensors provide a valuable measure of harmful fine particulate matter (PM 2.5 ), a significant portion of ambient PM 2.5 is typically the secondary product of air pollution emitted by varied sources outside of community boundaries. In contrast, concentrations of black carbon (BC), a component of PM 2.5 , are directly emitted by a few specific sources, such as diesel engines within communities. Motivated by community organizations seeking to understand persistent sources of local pollution, this study deployed a suite of custom-built BC sensors alongside a network of low-cost PM sensors for four weeks in two seasons at 50 stationary locations in the adjacent cities of Richmond, North Richmond, and San Pablo, California, east of the San Francisco Bay. Concentrations of BC varied more than PM 2.5 both temporally and spatially. Monthly network-average BC was 3×higher in winter than late spring, while PM 2.5 was only 10% lower. In both seasons, average PM 2.5 concentrations at two-thirds of sites were within ±10% of the network average, whereas two-thirds of sites had BC levels outside of ±10% of the network-average concentration. The most and least polluted locations were more persistent across seasons for BC than PM 2.5 , and the temporal dynamics of BC at these sites were similar, signifying that they are impacted by the same emission sources. Together, these spatiotemporal trends show that BC is a better indicator of the proximity and activity of local pollution sources than PM 2.5 . Thus, including BC in addition to PM 2.5 in community monitoring networks can provide additional insights about local sources of air pollution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Identification of aberrant circular RNA expression and its potential clinical value in primary great saphenous vein varicosities

Highlights: • This study identified 232 significantly aberrant circRNAs in primary great saphenous vein varicosities (PGSVVs). • A circRNA-miRNA-gene co-expression network was created. • Hsa{sub c}irc{sub 0}006427, hsa{sub c}irc{sub 0}089810 and hsa{sub c}irc{sub 0}005267 might be potential biological markers for PGSVVs. This study aimed to identify aberrant circRNA expression in primary great saphenous vein varicosities (PGSVVs) and investigate its potential clinical significance. High-throughput sequencing was applied to analyze the differential expression of circRNAs in three paired vein samples of PGSVVs and a control group. Computational bioinformatics analyses, including gene ontology (GO) analysis and encyclopedia of genes and genomes (KEGG) pathway analysis, were performed to further enrich microRNA data. Real-time quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was used to verify the selected aberrant circRNAs in all vein samples, and a receiver operating characteristic (ROC) curve was plotted to evaluate the diagnostic and potential clinical significance. A total of 232 circRNAs were significantly aberrantly expressed in PGSVVs, including 105 and 127 upregulated and downregulated circRNAs, respectively. The predicted top 10 downstream miRNAs of the significantly altered circRNAs are hsa-miR-103a-2-5p, hsa-miR-141-5p, hsa-miR-3692-5p, hsa-miR-4659a-3p, hsa-miR-4659b-3p, hsa-miR-4691-5p, hsa-miR-4778-3p, hsa-miR-6738-3p, hsa-miR-6792-3p and hsa-miR-6873-3p. GO analysis revealed that the most enriched and meaningful biological process, cellular component, and molecular function terms were related to the regulation of catabolic processes, the cytoplasm and ATP binding, respectively. The most enriched and meaningful pathways revealed by KEGG pathway analysis were related to “axon guidance” “vitamin digestion and absorption” and “NF-Kappa B signaling pathway”. Hsa{sub c}irc{sub 0}006427 (P = 0.007), hsa{sub c}irc{sub 0}089810 (P = 0.044) and hsa{sub c}irc{sub 0}005267 (P = 0.049) were significantly downregulated in the PGSVV group relative to their expression levels in the control group, and the area under the ROC curve was 0.9091, 0.8025 and 0.8148, respectively. This study demonstrated that circRNAs were differentially expressed in PGSVVs, and highlights the crucial roles of circRNAs in the pathogenesis of PGSVVs and indicates that hsa{sub c}irc{sub 0}006427, hsa{sub c}irc{sub 0}089810 and hsa{sub c}irc{sub 0}005267 might be potential diagnostic and clinical biological markers.

60 APPLIED LIFE SCIENCES↗