Variants of determining the construction production carbon footprint

Cilj ovog rada jest odrediti ugljični otisak gradnje po kubnom metru izgrađenog volumena zgrade. Za određivanje ugljičnog otiska odabrano je pet tipskih samostojećih kuća. One imaju ista materijalna svojstva, no razlikuju se po volumenu i izgrađenoj površini. Za određivanje ugljičnog otiska tijekom gradnje samostojećih kuća primijenjen je računalni program LCA (engl. Life Cyle Assesment - LCA). Na temelju tih izračuna određen je indikator proračuna po kubnom metru izgrađenog volumena građevine.The aim of the paper is to quantify the construction production carbon footprint per m3 of the built-up volume of the building. In order to determine the carbon footprint, 5 typical detached houses were selected. The individual buildings have the same material-construction characteristics; however, they differ in the size of the built-up volume, i.e. also in the built-up area. The LCA software was used to quantify the carbon footprint during the production phase of the model houses project. A budget indicator per m3 of the built-up volume was determined based on these calculations

Reliability prediction in early design stages

In the past, reliability is usually quantified with sufficient information available. This is not only time-consuming and cost-expensive, but also too late for occurred failures and losses. For solving this problem, the objective of this dissertation is to predict product reliability in early design stages with limited information. The current research of early reliability prediction is far from mature. Inspired by methodologies for the detail design stage, this research uses statistics-based and physics-based methodologies by providing general models with quantitative results, which could help design for reliability and decision making during the early design stage. New methodologies which accommodate component dependence, time dependence, and limited information are developed in this research to help early accurate reliability assessment. The component dependence is considered implicitly and automatically without knowing component design details by constructing a strength-stress interference model. The time-dependent reliability analysis is converted into its time-independent counterpart with the use of the extreme value of the system load by simulation. The effect of dependent interval distribution parameters estimated from limited point and interval samples are also considered to obtain more accurate system reliability. Optimization is used to obtain narrower system reliability bounds compared to those from the traditional method with independent component assumption or independent distribution parameter assumption. With new methodologies, it is possible to obtain narrower time-dependent system reliability bounds with limited information during early design stages by considering component dependence and distribution parameter dependence. Examples are provided to demonstrate the proposed methodologies --Abstract, page iv

Innovation report : a methodology for estimating gear pump wear-out reliability using pump pressure ripple and an extremely small sample size - the case study of a heavy-duty diesel engine lubrication gear pump

Design for Reliability (DfR) encourages testing products early in the New Product Development (NPD) process to identify and resolve weaknesses quickly. An organisation can then track reliability growth and intervene to ensure the changes in product robustness are in line with a timely release to market. However, for products with long life spans (such as a Heavy-Duty engine (HDE) lubrication gear pump), the evaluation of reliability with an extremely small number of prototype samples is problematic. Budget constraints, product size, and test facilities can limit the possibilities of accurately assessing the initial reliability forming a test planning paradox. The research in this thesis proposes an innovate methodology to minimise this test planning paradox, specific to a gear pump. The method uses step-stress accelerated degradation testing and Bayesian inference to estimate degradation parameters using only a sample size of two. Post-testing, numerical simulation is used to build a degradation model with larger sample sizes and produce a survival distribution at the quantile of interest. Increasing pump outlet pressure above normal usage accelerates the pump wear and pressure ripple measurements are used to monitor the performance degradation. On inspection, the pumps exhibit erosion on the housing and micro pitting of the gear flanks. The innovative use of a Maximal Overlap Discrete Wavelet Transforms (MODWT) with an Autoregressive Moving Average (ARMA 2,1) extracts a feature from the pressure ripple that provides a stochastic, linear and non-monotone degradation path that is appropriately modelled using a Brownian Motion simulation model. Regression analysis provides a drift and diffusion covariate functional relationship to pump outlet pressure. Given the stress-varying environment of an HDE, Monte Carlo simulations overcome the complexity of replicating vehicle drive cycle and produces a credible reliability estimate validated against a similarly designed high mileage pump. The application of this original methodology offers the opportunity to minimise the test planning paradox and satisfies populating the reliability growth chart. It is foreseen the method can be adopted for a wide range of positive displacement pumps where is it possible to measure pressure ripple