System-level Scenarios Research Articles

Is on-property heat and greywater recovery a sustainable option? A quantitative and qualitative assessment up to 2050

This article deals with ongoing attempts to recover heat and greywater at property level, based on an in-depth study of Stockholm, Sweden. We explore different socio-technical development paths from now up until 2050 using a novel combination of on-property technology case-studies, actor studies and system-level scenario evaluation, based on Artificial Neural Networks modelling. Our results show that the more conservative scenarios work in favour of large-scale actors while the more radical scenarios benefit the property owners. However, in the radical scenarios we identify disruptive effects on a system level due to disturbance on wastewater treatment plants, where incoming wastewater can be critically low for up to 120 days per year. At the same time, net energy savings are relatively modest (7.5% of heat demand) and economic gains for property owners small or uncertain. Current policies at EU and national level around energy-efficient buildings risk being counter-productive in cases when they push property owners to install wastewater heat recovery technology which, in places like Stockholm, can create suboptimal outcomes at the system level.

A method for evaluating and improving linear power flow models in system with large fluctuations

Linear power flow models are widely used in power system analysis to approximate nonlinear AC power flow equations. A fast and accurate error evaluation for linear power flow models is valuable in predicting error impact on decision-making and selecting appropriate linear power flow models for certain applications. Therefore, this paper focuses on the evaluation of line-form linear power flow models and proposes a novel method that enables a fast and accurate error evaluation for most linear power flow models that have fewer independent variables.In existing studies, linear power flow models are generally evaluated by Monte Carlo simulation method, in which it measures errors by using limited scenarios under certain conditions. Such evaluation method is enough for conventional power systems with low uncertainties. However, in systems with large fluctuations of renewable energy, the conventional Monte Carlo evaluation faces challenges. For example, a system with K uncertain loads requires at least 2K stochastic scenarios to represent the uncertainty by only considering the upper and the lower bounds of each uncertain load. This system-level scenario enumeration faces dimensionality curse and high computational burdens, especially for large-scale systems with high uncertainties.Given this difficulty, this paper proposes a novel evaluation method that defines the box-set evaluation ranges to avoid the dimensionality curse in system-level scenario enumerations. To achieve a fast evaluation, all algorithms in the proposed evaluation method are analytical. Besides, based on the evaluation method, a formulation for improving the accuracy of linear power flow models is proposed, whose analytical solution is also given. Several typical systems with different load levels are tested, and the results verify the effectiveness of the proposed method.

Design-Time Reliability Prediction Model for Component-Based Software Systems.

Software reliability is prioritised as the most critical quality attribute. Reliability prediction models participate in the prevention of software failures which can cause vital events and disastrous consequences in safety-critical applications or even in businesses. Predicting reliability during design allows software developers to avoid potential design problems, which can otherwise result in reconstructing an entire system when discovered at later stages of the software development life-cycle. Several reliability models have been built to predict reliability during software development. However, several issues still exist in these models. Current models suffer from a scalability issue referred to as the modeling of large systems. The scalability solutions usually come at a high computational cost, requiring solutions. Secondly, consideration of the nature of concurrent applications in reliability prediction is another issue. We propose a reliability prediction model that enhances scalability by introducing a system-level scenario synthesis mechanism that mitigates complexity. Additionally, the proposed model supports modeling of the nature of concurrent applications through adaption of formal statistical distribution toward scenario combination. The proposed model was evaluated using sensors-based case studies. The experimental results show the effectiveness of the proposed model from the view of computational cost reduction compared to similar models. This reduction is the main parameter for scalability enhancement. In addition, the presented work can enable system developers to know up to which load their system will be reliable via observation of the reliability value in several running scenarios.

System-Level Scenarios for the Elucidation of T Cell-Mediated Germinal Center B Cell Differentiation.

Germinal center (GC) reactions are vital to the correct functioning of the adaptive immune system, through formation of high affinity, class switched antibodies. GCs are transient anatomical structures in secondary lymphoid organs where specific B cells, after recognition of antigen and with T cell help, undergo class switching. Subsequently, B cells cycle between zones of proliferation and somatic hypermutation and zones where renewed antigen acquisition and T cell help allows for selection of high affinity B cells (affinity maturation). Eventually GC B cells first differentiate into long-lived memory B cells (MBC) and finally into plasma cells (PC) that partially migrate to the bone marrow to encapsulate into long-lived survival niches. The regulation of GC reactions is a highly dynamically coordinated process that occurs between various cells and molecules that change in their signals. Here, we present a system-level perspective of T cell-mediated GC B cell differentiation, presenting and discussing the experimental and computational efforts on the regulation of the GCs. We aim to integrate Systems Biology with B cell biology, to advance elucidation of the regulation of high-affinity, class switched antibody formation, thus to shed light on the delicate functioning of the adaptive immune system. Specifically, we: i) review experimental findings of internal and external factors driving various GC dynamics, such as GC initiation, maturation and GCBC fate determination; ii) draw comparisons between experimental observations and mathematical modeling investigations; and iii) discuss and reflect on current strategies of modeling efforts, to elucidate B cell behavior during the GC tract. Finally, perspectives are specifically given on to the areas where a Systems Biology approach may be useful to predict novel GCBC-T cell interaction dynamics.

Project-level accessibility analysis for land-use planning

The concept of accessibility has made inroads into planning practice, largely at the system level. That is, accessibility is measured or modeled for current or future regional transportation and land-use scenarios for evaluation or broad policy guidance. Yet system-level scenarios cannot readily be applied to the project-by-project decision-making that characterizes the majority of transportation and land-use planning decisions. Accessibility evaluation of individual transportation or land-development projects differs from system-level analysis in essential ways and thus requires specialized tools.This article proposes an elasticity-based metric of accessibility that can enable project-level evaluation of land-development projects as an accessibility-based alternative to traffic-impact analysis. The metric is demonstrated for three projects in Ann Arbor, Michigan, USA. The metric is shown to be sensitive to the location of development and capable of distinguishing among the analyzed projects in accessibility terms. Where mobility-based evaluation tends to rank peripheral development highly, the proposed accessibility metric appropriately rates central development as contributing the most to regional accessibility even after accounting for the traffic delay it engenders.

Simulating multimedia systems with MVPSIM

MVPSIM allows highly integrated system level simulations of complex, high-speed multimedia systems. It also aids multimedia software development by providing a uniform working environment to hardware architects and algorithm developers. MediaStation 5000 designers used MVPSIM to compare different architectures, testing and refining their design with various system level scenarios. MVPSIM can detect system modeling and design errors and provide accurate performance estimates of multimedia systems under development.