Model structure and uncertainty for stochastic non-point source modelling applications

The uncertainty associated with a rainfall-runoff and non-point source loading (NPS) model can be attributed to both the parameterization and model structure. An interesting implication of the areal nature of NPS models is the direct relationship between model structure (i.e. sub-watershed size) and sample size for the parameterization of spatial data. The approach of this research is to find structural limitations in scale for the use of the conceptual NPS model, then examine the scales at which suitable stochastic depictions of key parameter sets can be generated. The overlapping regions are optimal (and possibly the only suitable regions) for conducting meaningful stochastic analysis with a given NPS model. Previous work has sought to find optimal scales for deterministic analysis (where, in fact, calibration can be adjusted to compensate for sub-optimal scale selection); however, analysis of stochastic suitability and uncertainty associated with both the conceptual model and the parameter set, as presented here, is novel; as is the strategy of delineating a watershed based on the uncertainty distribution. The results of this paper demonstrate a narrow range of acceptable model structure for stochastic analysis in the chosen NPS model. In the case examined, the uncertainties associated with parameterization and parameter sensitivity are shown to be outweighed in significance by those resulting from structural and conceptual decisions. © 2011 Copyright IAHS Press.

The conceptual development of a simple scale-adaptive reactive pollutant dispersion model

The paper develops the basis for a self-consistent, operationally useful, reactive pollutant dispersion model, for application in urban environments. The model addresses the multi-scale nature of the physical and chemical processes and the interaction between the different scales. The methodology builds on existing techniques of source apportionment in pollutant dispersion and on reduction techniques of detailed chemical mechanisms. © 2005 Published by Elsevier Ltd.

Industrial ecology at factory level - A conceptual model

Growing environmental concerns caused by natural resource depletion and pollution need to be addressed. One approach to these problems is Sustainable Development, a key concept for our society to meet present as well as future needs worldwide. Manufacturing clearly has a major role to play in the move towards a more sustainable society. However it appears that basic principles of environmental sustainability are not systematically applied, with practice tending to focus on local improvements. The aim of the work presented in this paper is to adopt a more holistic view of the factory unit to enable opportunities for wider improvement. This research analyses environmental principles and industrial practice to develop a conceptual manufacturing ecosystem model as a foundation to improve environmental performance. The model developed focuses on material, energy and waste flows to better understand the interactions between manufacturing operations, supporting facilities and surrounding buildings. The research was conducted in three steps: (1) existing concepts and models for industrial sustainability were reviewed and environmental practices in manufacturing were collected and analysed; (2) gaps in knowledge and practice were identified; (3) the outcome is a manufacturing ecosystem model based on industrial ecology (IE). This conceptual model has novelty in detailing IE application at factory level and integrating all resource flows. The work is a base on which to build quantitative modelling tools to seek integrated solutions for lower resource input, higher resource productivity, fewer wastes and emissions, and lower operating cost within the boundary of a factory unit. © 2012 Elsevier Ltd. All rights reserved.

Spread of Salmonella enterica in the body during systemic infection: unravelling host and pathogen determinants.

Salmonella enterica causes a range of life-threatening diseases in humans and animals worldwide. Current treatments for S. enterica infections are not sufficiently effective, and there is a need to develop new vaccines and therapeutics. An understanding of how S. enterica spreads in tissues has very important implications for targeting bacteria with vaccine-induced immune responses and antimicrobial drugs. Development of new control strategies would benefit from a more sophisticated evaluation of bacterial location, spatiotemporal patterns of spread and distribution in the tissues, and sites of microbial persistence. We review here recent studies of S. enterica serovar Typhimurium (S. Typhimurium) infections in mice, an established model of systemic typhoid fever in humans, which suggest that continuous bacterial spread to new infection foci and host phagocytes is an essential trait in the virulence of S. enterica during systemic infections. We further highlight how infections within host tissues are truly heterogeneous processes despite the fact that they are caused by the expansion of a genetically homogeneous microbial population. We conclude by discussing how understanding the within-host quantitative, spatial and temporal dynamics of S. enterica infections might aid the development of novel targeted preventative measures and drug regimens.

An extended computational model of the circulatory system for designing ventricular assist devices.

An extended computational model of the circulatory system has been developed to predict blood flow in the presence of ventricular assist devices (VADs). A novel VAD, placed in the descending aorta, intended to offload the left ventricle (LV) and augment renal perfusion is being studied. For this application, a better understanding of the global hemodynamic response of the VAD, in essence an electrically driven pump, and the cardiovascular system is necessary. To meet this need, a model has been established as a nonlinear, lumped-parameter electrical analog, and simulated results under different states [healthy, congestive heart failure (CHF), and postinsertion of VAD] are presented. The systemic circulation is separated into five compartments and the descending aorta is composed of three components to accurately yield the system response of each section before and after the insertion of the VAD. Delays in valve closing time and blood inertia in the aorta were introduced to deliver a more realistic model. Pump governing equations and optimization are based on fundamental theories of turbomachines and can serve as a practical initial design point for rotary blood pumps. The model's results closely mimic established parameters for the circulatory system and confirm the feasibility of the intra-aortic VAD concept. This computational model can be linked with models of the pump motor to provide a valuable tool for innovative VAD design.

Mapping the conceptual design activity of interdisciplinary teams

The conceptual design phase of any project is, by its very nature, a vibrant, creative and dynamic period. It can also be disorganized with much backtracking accompanying the exchange of information between design team members. The transfer of information, ideas and opinion is critical to the development of concepts and as such, rather than being recognized as merely a component of conceptual design activity, it needs to be understood and, ultimately, managed. This paper describes an experimental workshop involving fifteen design professionals in which conceptual design activity was tracked, and subsequently mapped, in order to test and validate a tentative design framework (phase and activity model). The nature of the design progression of the various teams is captured and analyzed, allowing a number of conclusions to be drawn regarding both the iterative nature of this phase of design and how teams of professionals actually design together.