GPS-only gravity field determination from GOCE data

The Gravity field and steady-state Ocean Circulation Explorer (GOCE) is now in orbit for more than four years. This is longer than the originally planned lifetime of the satellite and after three years on the same altitude the satellite has been lowered to 235 km in several steps. In the frame of the GOCE High-level Processing Facility the Astronomical Institute of the University of Bern (AIUB) is responsible for the determination of the official Precise Science Orbit (PSO) product. Kinematic GOCE orbits are part of this product and are used by several institutions in- and outside the HPF for determining the low degrees of the Earth’s gravity field. AIUB GOCE GPS-only gravity field solutions using the Celestial Mechanics Approach and covering the Release 4 period as well as a more recent time interval at the lower orbit altitude are shown and discussed. Special attention is paid to the impact of systematic deficiencies in the kinematic orbits on the resulting gravity fields, e.g., related to the geomagnetic equator, and on possibilities to get rid of them.

GOCE: precise orbit determination for the entire mission

The Gravity field and steady-state Ocean Circulation Explorer (GOCE) was the first Earth explorer core mission of the European Space Agency. It was launched on March 17, 2009 into a Sun-synchronous dusk-dawn orbit and re-entered into the Earth’s atmosphere on November 11, 2013. The satellite altitude was between 255 and 225 km for the measurement phases. The European GOCE Gravity consortium is responsible for the Level 1b to Level 2 data processing in the frame of the GOCE High-level processing facility (HPF). The Precise Science Orbit (PSO) is one Level 2 product, which was produced under the responsibility of the Astronomical Institute of the University of Bern within the HPF. This PSO product has been continuously delivered during the entire mission. Regular checks guaranteed a high consistency and quality of the orbits. A correlation between solar activity, GPS data availability and quality of the orbits was found. The accuracy of the kinematic orbit primarily suffers from this. Improvements in modeling the range corrections at the retro-reflector array for the SLR measurements were made and implemented in the independent SLR validation for the GOCE PSO products. The satellite laser ranging (SLR) validation finally states an orbit accuracy of 2.42 cm for the kinematic and 1.84 cm for the reduced-dynamic orbits over the entire mission. The common-mode accelerations from the GOCE gradiometer were not used for the official PSO product, but in addition to the operational HPF work a study was performed to investigate to which extent common-mode accelerations improve the reduced-dynamic orbit determination results. The accelerometer data may be used to derive realistic constraints for the empirical accelerations estimated for the reduced-dynamic orbit determination, which already improves the orbit quality. On top of that the accelerometer data may further improve the orbit quality if realistic constraints and state-of-the-art background models such as gravity field and ocean tide models are used for the reduced-dynamic orbit determination.

GOCE precise orbit determination for the entire Mission – challenges in the final mission phase

The Gravity field and steady-state Ocean Circulation Explorer (GOCE), ESA’s first Earth Explorer core mission, was launched on March 17, 2009 into a sunsynchronous dusk-dawn orbit and eventually re-entered into the Earth’s atmosphere on November 11, 2013. A precise science orbit (PSO) product was provided by the GOCE High-level Processing Facility (HPF) from the GPS high-low Satellite-to-Satellite Tracking (hl-SST) data from the beginning until the very last days of the mission. We recapitulate the PSO procedure and refer to the results achieved until the official end of the GOCE mission on October 21, 2013, where independent validations with Satellite Laser ranging (SLR) measurements confirmed a high quality of the PSO product of about 2 cm 1-D RMS. We then focus on the period after the official end of the mission, where orbits could still be determined thanks to the continuously running GPS receivers delivering high quality data until a few hours before the re-entry into the Earth’s atmosphere. We address the challenges encountered for orbit determination during these last days and report on adaptions in the PSO procedure to also obtain good orbit results at the unprecedented low orbital altitudes below 224 km.

Data and Documentation

The primary aims of this survey were to assess household waste management practices; participation in waste diversion practices; knowledge of local waste management politics; willingness to participate in local decision making regarding the development of a local waste processing facility; attitudes and perceptions of waste, waste management policies, and waste management technologies.

Data and Documentation

The primary aims of this survey were to assess household waste management practices; participation in waste diversion practices; knowledge of local waste management politics; willingness to participate in local decision making regarding the development of a local waste processing facility; attitudes and perceptions of waste, waste management policies, and waste management technologies.

Test facility inventory data processing system - procedure.

National Highway Safety Bureau, Washington, D.C.

The design and engineering of a reactor test facility for thermal processing of biomass

This thesis describes the design and engineering of a pressurised biomass gasification test facility. A detailed examination of the major elements within the plant has been undertaken in relation to specification of equipment, evaluation of options and final construction. The retrospective project assessment was developed from consideration of relevant literature and theoretical principles. The literature review includes a discussion on legislation and applicable design codes. From this analysis, each of the necessary equipment units was reviewed and important design decisions and procedures highlighted and explored. Particular emphasis was placed on examination of the stringent demands of the ASME VIII design codes. The inter-relationship of functional units was investigated and areas of deficiency, such as biomass feeders and gas cleaning, have been commented upon. Finally, plant costing was summarized in relation to the plant design and proposed experimental programme. The main conclusion drawn from the study is that pressurised gasification of biomass is far more difficult and expensive to support than atmospheric gasification. A number of recommendations have been made regarding future work in this area.

Determination of volatiles produced during radiation processing in Laurus cinnamomum

In order to protect food from pathogenic microorganisms as well as increase its shelf-life, while keeping sensorial properties (e.g., odor and taste), which are important properties required by spice buyers, it is necessary to analyze volatile formation from irradiation of medicinal and food herbs. Possible changes in the odor of these herbs are evaluated by characterizing different radiation doses and effects on sensorial properties, in order to allow better application of the irradiation technology. The aim of the present study was to analyze volatile formation on cinnamon (Laurus cinnamomum) samples after gamma irradiation. These samples were irradiated into plastic packages using a (60)Co facility. Radiation doses applied were 0, 5, 10, 15, 20 and 25 kGy. For the analysis of the samples, solid-phase microextraction (SPME) was applied, while for the analysis of volatile compounds, CG/MS. Spice irradiation showed the highest decrease in volatile compounds. For L. cinnamomum, the irradiation decreased volatile compounds by nearly 56% and 89.5%, respectively, comparing to volatile from a sample which had not been previously irradiated. Crown Copyright (C) 2009 Published by Elsevier Ltd. All rights reserved.

The sample processing time interval as an influential factor in flow cytometry analysis of lymphocyte subsets

The objective of this paper is to propose a protocol to analyze blood samples in yellow fever 17DD vaccinated which developed serious adverse events. We investigated whether or not the time between sample collection and sample processing could interfere in lymphocyte subset percentage, for it is often impossible to analyze blood samples immediately after collection due to transport delay from collection places to the flow cytometry facility. CD4+CD38+ T, CD8+CD38+ T, CD3+ T, CD19+ B lymphocyte subsets were analyzed by flow cytometry in nine healthy volunteers immediately after blood collection and after intervals of 24 and 48 h. The whole blood lysis method and gradient sedimentation by Histopaque were applied to isolate peripheral blood mononuclear cells for flow cytometry analyses. With the lysis method, there was no significant change in lymphocyte subset percentage between the two time intervals (24 and 48 h). In contrast, when blood samples were processed by Histopaque gradient sedimentation, time intervals for sample processing influenced the percentage in T lymphocyte subsets but not in B cells. From the results obtained, we could conclude that the whole blood lysis method is more appropriate than gradient sedimentation by Histopaque for immunophenotyping of blood samples collected after serious adverse events, due to less variation in the lymphocyte subset levels with respect to the time factor.

A decision support system for cost determination in grain storage facility operations

Many research works have being carried out on analyzing grain storage facility costs; however a few of them had taken into account the analysis of factors associated to all pre-processing and storage steps. The objective of this work was to develop a decision support system for determining the grain storage facility costs and utilization fees in grain storage facilities. The data of a CONAB storage facility located in Ponta Grossa - PR, Brazil, was used as input of the system developed to analyze its specific characteristics, such as amount of product received and stored throughout the year, hourly capacity of drying, cleaning, and receiving, and dispatch. By applying the decision support system, it was observed that the reception and expedition costs were exponentially reduced as the turnover rate of the storage increased. The cleaning and drying costs increased linearly with grain initial moisture. The storage cost increased exponentially as the occupancy rate of the storage facility decreased.

Chemical characterization of a dye processing plant effluent - Identification of the mutagenic components

This work shows the chemical characterization of a dye processing plant effluent that was contributing to the mutagenicity previously detected in the Cristais river, São Paulo, Brazil, that had an impact on the quality of the related drinking water. The mutagenic dyes Disperse Blue 373, Disperse Orange 37 and Disperse Violet 93, components of a Black Dye Commercial Product (BDCP) frequently used by the facility, were detected by thin layer chromatography (TLC). The blue and orange dyes were quantified by high performance liquid chromatography (HPLC/DAD) in a raw and treated effluent samples and their contribution to the mutagenicity was calculated based on the potency of each dye for the Salmonella YG1041. In the presence of S9 the Disperse Blue 373 accounted for 2.3% of the mutagenic activity of the raw and 71.5% of the treated effluent. In the absence of S9 the Disperse Blue 373 accounted for 1.3% of the mutagenic activity of the raw and 1.5% of the treated effluent. For the Disperse Orange 37, in the presence of S9, it contributed for 0.5% of the mutagenicity of the raw and 6% of the treated effluent. In the absence of S9; 11.5% and 4.4% of the raw and treated effluent mutagenicity, respectively. The contribution of the Disperse Violet 93 was not evaluated because this compound could not be quantified by HPLC/DAD. Mutagenic and/or carcinogenic aromatic amines were also preliminary detected using gas chromatograph/mass spectrometry in both raw and treated and are probably accounting for part of the observed mutagenicity. The effluent treatment applied by the industry does not seem to remove completely the multagenic compounds. The Salmomella/microsome assay coupled with TLC analysis seems to be an important tool to monitor the efficiency of azo dye processing plant effluent treatments. (c) 2006 Elsevier B.V. All rights reserved.

A priori reformulations for joint rolling-horizon scheduling of materials processing and lot-sizing problem

In many production processes, a key material is prepared and then transformed into different final products. The lot sizing decisions concern not only the production of final products, but also that of material preparation in order to take account of their sequence-dependent setup costs and times. The amount of research in recent years indicates the relevance of this problem in various industrial settings. In this paper, facility location reformulation and strengthening constraints are newly applied to a previous lot-sizing model in order to improve solution quality and computing time. Three alternative metaheuristics are used to fix the setup variables, resulting in much improved performance over previous research, especially regarding the use of the metaheuristics for larger instances. © 2013 Elsevier Ltd. All rights reserved.

Development of an optimization model for biofuel facility size and location and a simulation model for design of a biofuel supply chain

To mitigate greenhouse gas (GHG) emissions and reduce U.S. dependence on imported oil, the United States (U.S.) is pursuing several options to create biofuels from renewable woody biomass (hereafter referred to as “biomass”). Because of the distributed nature of biomass feedstock, the cost and complexity of biomass recovery operations has significant challenges that hinder increased biomass utilization for energy production. To facilitate the exploration of a wide variety of conditions that promise profitable biomass utilization and tapping unused forest residues, it is proposed to develop biofuel supply chain models based on optimization and simulation approaches. The biofuel supply chain is structured around four components: biofuel facility locations and sizes, biomass harvesting/forwarding, transportation, and storage. A Geographic Information System (GIS) based approach is proposed as a first step for selecting potential facility locations for biofuel production from forest biomass based on a set of evaluation criteria, such as accessibility to biomass, railway/road transportation network, water body and workforce. The development of optimization and simulation models is also proposed. The results of the models will be used to determine (1) the number, location, and size of the biofuel facilities, and (2) the amounts of biomass to be transported between the harvesting areas and the biofuel facilities over a 20-year timeframe. The multi-criteria objective is to minimize the weighted sum of the delivered feedstock cost, energy consumption, and GHG emissions simultaneously. Finally, a series of sensitivity analyses will be conducted to identify the sensitivity of the decisions, such as the optimal site selected for the biofuel facility, to changes in influential parameters, such as biomass availability and transportation fuel price. Intellectual Merit The proposed research will facilitate the exploration of a wide variety of conditions that promise profitable biomass utilization in the renewable biofuel industry. The GIS-based facility location analysis considers a series of factors which have not been considered simultaneously in previous research. Location analysis is critical to the financial success of producing biofuel. The modeling of woody biomass supply chains using both optimization and simulation, combing with the GIS-based approach as a precursor, have not been done to date. The optimization and simulation models can help to ensure the economic and environmental viability and sustainability of the entire biofuel supply chain at both the strategic design level and the operational planning level. Broader Impacts The proposed models for biorefineries can be applied to other types of manufacturing or processing operations using biomass. This is because the biomass feedstock supply chain is similar, if not the same, for biorefineries, biomass fired or co-fired power plants, or torrefaction/pelletization operations. Additionally, the research results of this research will continue to be disseminated internationally through publications in journals, such as Biomass and Bioenergy, and Renewable Energy, and presentations at conferences, such as the 2011 Industrial Engineering Research Conference. For example, part of the research work related to biofuel facility identification has been published: Zhang, Johnson and Sutherland [2011] (see Appendix A). There will also be opportunities for the Michigan Tech campus community to learn about the research through the Sustainable Future Institute.

DEVELOPMENT OF AN OPTIMIZATION MODEL FOR BIOFUEL FACILITY SIZE AND LOCATION AND A SIMULATION MODEL FOR DESIGN OF A BIOFUEL SUPPLY CHAIN

A range of societal issues have been caused by fossil fuel consumption in the transportation sector in the United States (U.S.), including health related air pollution, climate change, the dependence on imported oil, and other oil related national security concerns. Biofuels production from various lignocellulosic biomass types such as wood, forest residues, and agriculture residues have the potential to replace a substantial portion of the total fossil fuel consumption. This research focuses on locating biofuel facilities and designing the biofuel supply chain to minimize the overall cost. For this purpose an integrated methodology was proposed by combining the GIS technology with simulation and optimization modeling methods. The GIS based methodology was used as a precursor for selecting biofuel facility locations by employing a series of decision factors. The resulted candidate sites for biofuel production served as inputs for simulation and optimization modeling. As a precursor to simulation or optimization modeling, the GIS-based methodology was used to preselect potential biofuel facility locations for biofuel production from forest biomass. Candidate locations were selected based on a set of evaluation criteria, including: county boundaries, a railroad transportation network, a state/federal road transportation network, water body (rivers, lakes, etc.) dispersion, city and village dispersion, a population census, biomass production, and no co-location with co-fired power plants. The simulation and optimization models were built around key supply activities including biomass harvesting/forwarding, transportation and storage. The built onsite storage served for spring breakup period where road restrictions were in place and truck transportation on certain roads was limited. Both models were evaluated using multiple performance indicators, including cost (consisting of the delivered feedstock cost, and inventory holding cost), energy consumption, and GHG emissions. The impact of energy consumption and GHG emissions were expressed in monetary terms to keep consistent with cost. Compared with the optimization model, the simulation model represents a more dynamic look at a 20-year operation by considering the impacts associated with building inventory at the biorefinery to address the limited availability of biomass feedstock during the spring breakup period. The number of trucks required per day was estimated and the inventory level all year around was tracked. Through the exchange of information across different procedures (harvesting, transportation, and biomass feedstock processing procedures), a smooth flow of biomass from harvesting areas to a biofuel facility was implemented. The optimization model was developed to address issues related to locating multiple biofuel facilities simultaneously. The size of the potential biofuel facility is set up with an upper bound of 50 MGY and a lower bound of 30 MGY. The optimization model is a static, Mathematical Programming Language (MPL)-based application which allows for sensitivity analysis by changing inputs to evaluate different scenarios. It was found that annual biofuel demand and biomass availability impacts the optimal results of biofuel facility locations and sizes.