Assessment Of Dynamic Properties Of A Crowd Model For Human-Structure Interaction Modeling

As lightweight and slender structural elements are more frequently used in the design, large scale structures become more flexible and susceptible to excessive vibrations. To ensure the functionality of the structure, dynamic properties of the occupied structure need to be estimated during the design phase. Traditional analysis method models occupants simply as an additional mass; however, research has shown that human occupants could be better modeled as an additional degree-of- freedom. In the United Kingdom, active and passive crowd models are proposed by the Joint Working Group as a result of a series of analytical and experimental research. It is expected that the crowd models would yield a more accurate estimation to the dynamic response of the occupied structure. However, experimental testing recently conducted through a graduate student project at Bucknell University indicated that the proposed passive crowd model might be inaccurate in representing the impact on the structure from the occupants. The objective of this study is to provide an assessment of the validity of the crowd models proposed by JWG through comparing the dynamic properties obtained from experimental testing data and analytical modeling results. The experimental data used in this study was collected by Firman in 2010. The analytical results were obtained by performing a time-history analysis on a finite element model of the occupied structure. The crowd models were created based on the recommendations from the JWG combined with the physical properties of the occupants during the experimental study. During this study, SAP2000 was used to create the finite element models and to implement the analysis; Matlab and ME¿scope were used to obtain the dynamic properties of the structure through processing the time-history analysis results from SAP2000. The result of this study indicates that the active crowd model could quite accurately represent the impact on the structure from occupants standing with bent knees while the passive crowd model could not properly simulate the dynamic response of the structure when occupants were standing straight or sitting on the structure. Future work related to this study involves improving the passive crowd model and evaluating the crowd models with full-scale structure models and operating data.

Advantages and Applications of Transforming Empirical Model Input Space with Dimensional Models

Model-based calibration of steady-state engine operation is commonly performed with highly parameterized empirical models that are accurate but not very robust, particularly when predicting highly nonlinear responses such as diesel smoke emissions. To address this problem, and to boost the accuracy of more robust non-parametric methods to the same level, GT-Power was used to transform the empirical model input space into multiple input spaces that simplified the input-output relationship and improved the accuracy and robustness of smoke predictions made by three commonly used empirical modeling methods: Multivariate Regression, Neural Networks and the k-Nearest Neighbor method. The availability of multiple input spaces allowed the development of two committee techniques: a 'Simple Committee' technique that used averaged predictions from a set of 10 pre-selected input spaces chosen by the training data and the "Minimum Variance Committee" technique where the input spaces for each prediction were chosen on the basis of disagreement between the three modeling methods. This latter technique equalized the performance of the three modeling methods. The successively increasing improvements resulting from the use of a single best transformed input space (Best Combination Technique), Simple Committee Technique and Minimum Variance Committee Technique were verified with hypothesis testing. The transformed input spaces were also shown to improve outlier detection and to improve k-Nearest Neighbor performance when predicting dynamic emissions with steady-state training data. An unexpected finding was that the benefits of input space transformation were unaffected by changes in the hardware or the calibration of the underlying GT-Power model.

Creation of Computer Simulation Model for Ecological Consequences Prognosis of Toxic Chemicals Discharge from Sunken on Baltic Sea Bottom Weapons"

This study summarises all the accessible data on old German chemical weapons dumped in the Baltic Sea. Mr. Goncharov formulated a concept of ecological impact evaluation of chemical warfare agents (CWA) on the marine environment and structured a simulation model adapted to the specific character of the hydrological condition and hydrobiological subjects of the Bornholm Deep. The mathematical model he has created describes the spreading of contaminants by currents and turbulence in the near bottom boundary layer. Parameters of CWA discharge through corrosion of canisters were given for various kinds of bottom sediments with allowance for current velocity. He created a method for integral estimations and a computer simulation model and completed a forecast for CWA "Mustard", which showed that in normal hydrometeorological conditions there are local toxic plumes drifting along the bottom for a distance of up to several kilometres. With storm winds the toxic plumes from separate canisters interflow and lengthen and can reach fishery areas near Bornholm Island. When salt water from the North Sea flows in, the length of toxic zones can increase up to and over 100 kilometres and toxic water masses can spread into the northern Baltic. On this basis, Mr. Goncharov drew up recommendations to reduce dangers for human ecology and proposed the creation of a special system for the forecasting and remote sensing of the environmental conditions of CWA burial places.

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 A CONCEPTUAL MODEL AND PARAMETERIZATION OF A MATHEMATICAL MODEL FOR SEDIMENT PHOSPHORUS DIAGENESIS, SORPTION AND RELEASE FROM ONONDAGA LAKE SYRACUSE, NEW YORK

Eutrophication is a persistent problem in many fresh water lakes. Delay in lake recovery following reductions in external loading of phosphorus, the limiting nutrient in fresh water ecosystems, is often observed. Models have been created to assist with lake remediation efforts, however, the application of management tools to sediment diagenesis is often neglected due to conceptual and mathematical complexity. SED2K (Chapra et al. 2012) is proposed as a "middle way", offering engineering rigor while being accessible to users. An objective of this research is to further support the development and application SED2K for sediment phosphorus diagenesis and release to the water column of Onondaga Lake. Application of SED2K has been made to eutrophic Lake Alice in Minnesota. The more homogenous sediment characteristics of Lake Alice, compared with the industrially polluted sediment layers of Onondaga Lake, allowed for an invariant rate coefficient to be applied to describe first order decay kinetics of phosphorus. When a similar approach was attempted on Onondaga Lake an invariant rate coefficient failed to simulate the sediment phosphorus profile. Therefore, labile P was accounted for by progressive preservation after burial and a rate coefficient which gradual decreased with depth was applied. In this study, profile sediment samples were chemically extracted into five operationally-defined fractions: CaCO3-P, Fe/Al-P, Biogenic-P, Ca Mineral-P and Residual-P. Chemical fractionation data, from this study, showed that preservation is not the only mechanism by which phosphorus may be maintained in a non-reactive state in the profile. Sorption has been shown to contribute substantially to P burial within the profile. A new kinetic approach involving partitioning of P into process based fractions is applied here. Results from this approach indicate that labile P (Ca Mineral and Organic P) is contributing to internal P loading to Onondaga Lake, through diagenesis and diffusion to the water column, while the sorbed P fraction (Fe/Al-P and CaCO3-P) is remaining consistent. Sediment profile concentrations of labile and total phosphorus at time of deposition were also modeled and compared with current labile and total phosphorus, to quantify the extent to which remaining phosphorus which will continue to contribute to internal P loading and influence the trophic status of Onondaga Lake. Results presented here also allowed for estimation of the depth of the active sediment layer and the attendant response time as well as the sediment burden of labile P and associated efflux.

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.

Dynamics of a minimal model of interlocked positive and negative feedback loops of transcriptional regulation by cAMP-response element binding proteins.

cAMP-response element binding (CREB) proteins are involved in transcriptional regulation in a number of cellular processes (e.g., neural plasticity and circadian rhythms). The CREB family contains activators and repressors that may interact through positive and negative feedback loops. These loops can be generated by auto- and cross-regulation of expression of CREB proteins, via CRE elements in or near their genes. Experiments suggest that such feedback loops may operate in several systems (e.g., Aplysia and rat). To understand the functional implications of such feedback loops, which are interlocked via cross-regulation of transcription, a minimal model with a positive and negative loop was developed and investigated using bifurcation analysis. Bifurcation analysis revealed diverse nonlinear dynamics (e.g., bistability and oscillations). The stability of steady states or oscillations could be changed by time delays in the synthesis of the activator (CREB1) or the repressor (CREB2). Investigation of stochastic fluctuations due to small numbers of molecules of CREB1 and CREB2 revealed a bimodal distribution of CREB molecules in the bistability region. The robustness of the stable HIGH and LOW states of CREB expression to stochastic noise differs, and a critical number of molecules was required to sustain the HIGH state for days or longer. Increasing positive feedback or decreasing negative feedback also increased the lifetime of the HIGH state, and persistence of this state may correlate with long-term memory formation. A critical number of molecules was also required to sustain robust oscillations of CREB expression. If a steady state was near a deterministic Hopf bifurcation point, stochastic resonance could induce oscillations. This comparative analysis of deterministic and stochastic dynamics not only provides insights into the possible dynamics of CREB regulatory motifs, but also demonstrates a framework for understanding other regulatory processes with similar network architecture.

Dynamics of a minimal model of interlocked positive and negative feedback loops of transcriptional regulation by cAMP-response element binding proteins.

cAMP-response element binding (CREB) proteins are involved in transcriptional regulation in a number of cellular processes (e.g., neural plasticity and circadian rhythms). The CREB family contains activators and repressors that may interact through positive and negative feedback loops. These loops can be generated by auto- and cross-regulation of expression of CREB proteins, via CRE elements in or near their genes. Experiments suggest that such feedback loops may operate in several systems (e.g., Aplysia and rat). To understand the functional implications of such feedback loops, which are interlocked via cross-regulation of transcription, a minimal model with a positive and negative loop was developed and investigated using bifurcation analysis. Bifurcation analysis revealed diverse nonlinear dynamics (e.g., bistability and oscillations). The stability of steady states or oscillations could be changed by time delays in the synthesis of the activator (CREB1) or the repressor (CREB2). Investigation of stochastic fluctuations due to small numbers of molecules of CREB1 and CREB2 revealed a bimodal distribution of CREB molecules in the bistability region. The robustness of the stable HIGH and LOW states of CREB expression to stochastic noise differs, and a critical number of molecules was required to sustain the HIGH state for days or longer. Increasing positive feedback or decreasing negative feedback also increased the lifetime of the HIGH state, and persistence of this state may correlate with long-term memory formation. A critical number of molecules was also required to sustain robust oscillations of CREB expression. If a steady state was near a deterministic Hopf bifurcation point, stochastic resonance could induce oscillations. This comparative analysis of deterministic and stochastic dynamics not only provides insights into the possible dynamics of CREB regulatory motifs, but also demonstrates a framework for understanding other regulatory processes with similar network architecture.

THE EXPRESSION PROFILE OF A GWAS DETECTED GENE (NINJ2) IN THE BRAIN OF A MOUSE MODEL OF ISCHEMIC STROKE

Stroke is the third leading cause of death and a major debilitating disease in the United States. Multiple factors, including genetic factors, contribute to the development of the disease. Genome-wide association studies (GWAS) have contributed to the identification of genetic loci influencing risk for complex diseases, such as stroke. In 2010, a GWAS of incident stroke was performed in four large prospective cohorts from the USA and Europe and identified an association of two Single Nucleotide Polymorphisms (SNPs) on chromosome 12p13 with a greater risk of ischemic stroke in individuals of European and African-American ancestry. These SNPs are located 11 Kb upstream of the nerve injury-induced gene 2, Ninjurin2 (NINJ2), suggesting that this gene may be involved in stroke pathogenesis. NINJ2 is a cell adhesion molecule induced in the distal glial cells from a sciatic-nerve injury at 7-days after injury. In an effort to ascribe a possible role of NINJ2 in stroke, we have assessed changes in the level of gene and protein expression of NINJ2 following a time-course from a transiently induced middle cerebral artery ischemic stroke in mice brains. We report an increase in the gene expression of NINJ2 in the ischemic and peri-infarct (ipsilateral) cortical tissues at 7 and 14-days after stroke. We also report an increase in the protein expression of NINJ2 in the cortex of both the ipsilateral and contralateral cortical tissues at the same time-points. We conclude that the expression of NINJ2 is regulated by an ischemic stroke in the cortex and is consistent with NINJ2 being involved in the recovery time-points of stroke.

Development of a conceptual model for mass gatherings

In making the arrangements for the visit of Pope John Paul II to San Antonio, Texas, in September, 1987, it was discovered that no comprehensive documents or guidelines are available in the public sector for planning such an event. It was not clear which, if any, laws applied. The literature describes rock concerts, papal masses, and civil disorders. These events are held in stadia, and in the open. There was little agreement on what services, if any, were needed to protect the public's health and the environment; or if needed, how services should be provided, or by whom.^ A literature review and bibliography are given to provide greater understanding of the variety of mass gatherings and the many factors that impinge on temporary groups while away from their homes. Descriptions of past mass gatherings in terms of personnel ratios are provided. This study develops a conceptual model which delineates some of the known parameters necessary for successfully conducting a mass gathering. A study of one such site is given.^ Provisions for public wellness and freedom from disease at a mass gathering include adequate water (fluids), food, sanitary facilities, security, transportation, and medical services. The determination of adequacy of these provisions is discussed. Methods of determining the use of provided facilities are given. ^

RESPIRATORY COMPENSATION MECHANISMS IN THE UPPER AND LOWER RESPIRATORY TRACTS OF AN ANIMAL MODEL AFTER SUBCHRONIC INHALATION EXPOSURE TO FORMALDEHYDE: IMPLICATIONS FOR TOXICOLOGY RISK ASSESSMENT (DEPOSITION, DOSE RECEIVED, RESPONSE)

The potential for significant human populations to experience long-term inhalation of formaldehyde and reports of symptomatology due to this exposure has led to a considerable interest in the toxicologic assessment of risk from subchronic formaldehyde exposures using animal models. Since formaldehyde inhalation depresses certain respiratory parameters in addition to its other forms of toxicity, there is a potential for the alteration of the actual dose received by the exposed individual (and the resulting toxicity) due to this respiratory effect. The respiratory responses to formaldehyde inhalation and the subsequent pattern of deposition were therefore investigated in animals that had received subchronic exposure to the compound, and the potential for changes in the formaldehyde dose received due to long-term inhalation evaluated. Male Sprague-Dawley rats were exposed to either 0, 0.5, 3, or 15 ppm formaldehyde for 6 hours/day, 5 days/week for up to 6 months. The patterns of respiratory response, deposition and the compensation mechanisms involved were then determined in a series of formaldehyde test challenges to both the upper and to the lower respiratory tracts in separate groups of subchronically exposed animals and age-specific controls (four concentration groups, two time points). In both the control and pre-exposed animals, there was a characteristic recovery of respiratory parameters initially depressed by formaldehyde inhalation to at or approaching pre-exposure levels within 10 minutes of the initiation of exposure. Also, formaldehyde deposition was found to remain very high in the upper and lower tracts after long-term exposure. Therefore, there was probably little subsequent effect on the dose received by the exposed individual that was attributable to the repeated exposures. There was a diminished initial minute volume response in test challenges of both the upper and lower tracts of animals that had received at least 16 weeks of exposure to 15 ppm, with compensatory increases in tidal volume in the upper tract and respiratory rate in the lower tract. However, this dose-related effect was probably not relevant to human risk estimation because this formaldehyde dose is in excess of that experienced by human populations. ^

Metropolitan Observatory for Street Children and Youngsters: A Chilean Experience of an Innovative Model

In Chile, street children and youngsters' situations have changed significantly over the last decades. The Metropolitan Observatory is an innovative organization that makes it possible to follow this velnerable group. The Observatory is becoming a pioneering actor in the subject, thanks to the participative work and agreed consensus of different institutions involved. The aim of this paper is to introduce the innovative cross-sectoral work done by the Metropolitan Observatory for street children and youth.