J. H. G. Vreeburg

Bio: J. H. G. Vreeburg is an academic researcher from Wageningen University and Research Centre. The author has contributed to research in topics: Stochastic modelling & Settling. The author has an hindex of 12, co-authored 13 publications receiving 753 citations. Previous affiliations of J. H. G. Vreeburg include Delft University of Technology.

Simulating Residential Water Demand with a Stochastic End-Use Model

Abstract: A water demand end-use model was developed to predict water demand patterns with a small time scale (1 s) and small spatial scale (residence level). The end-use model is based on statistical inform...

A fully adaptive forecasting model for short-term drinking water demand

Abstract: For the optimal control of a water supply system, a short-term water demand forecast is necessary. We developed a model that forecasts the water demand for the next 48 h with 15-min time steps. The model uses measured water demands and static calendar data as single input. Based on this input, the model fully adaptively derives day factors and daily demand patterns for the seven days of the week, and for a configurable number of deviant day types. Although not using weather data as input, the model is able to identify occasional extra water demand in the evening during fair weather periods, and to adjust the forecast accordingly. The model was tested on datasets containing six years of water demand data in six different areas in the central and Southern part of Netherlands. The areas have all the same moderate weather conditions, and vary in size from very large (950,000 inhabitants) to small (2400 inhabitants). The mean absolute percentage error (MAPE) for the 24-h forecasts varied between 1.44 and 5.12%, and for the 15-min time step forecasts between 3.35 and 10.44%. The model is easy to implement, fully adaptive and accurate, which makes it suitable for application in real time control.

Introduction to quality engineering. designing quality into products a

Abstract: Contents: Variety and Quality. Variability loss and tolerance. Determining tolerances. Tolerance design and experimental design. Offline and online quality control. Parameter design and tolerance design: case study. Experimental design for smaller is better characteristics. Experimental design for larger is better characteristics. Bypassing the S/N ratio: spring experiment. Experimental design for dynamic characteristics.

Biological Stability of Drinking Water: Controlling Factors, Methods, and Challenges

Abstract: Biological stability of drinking water refers to the concept of providing consumers with drinking water of same microbial quality at the tap as produced at the water treatment facility. However, uncontrolled growth of bacteria can occur during distribution in water mains and premise plumbing, and can lead to hygienic (e.g., development of opportunistic pathogens), aesthetic (e.g., deterioration of taste, odor, color) or operational (e.g., fouling or biocorrosion of pipes) problems. Drinking water contains diverse microorganisms competing for limited available nutrients for growth. Bacterial growth and interactions are regulated by factors, such as (i) type and concentration of available organic and inorganic nutrients, (ii) type and concentration of residual disinfectant, (iii) presence of predators, such as protozoa and invertebrates, (iv) environmental conditions, such as water temperature, and (v) spatial location of microorganisms (bulk water, sediment, or biofilm). Water treatment and distribution conditions in water mains and premise plumbing affect each of these factors and shape bacterial community characteristics (abundance, composition, viability) in distribution systems. Improved understanding of bacterial interactions in distribution systems and of environmental conditions impact is needed for better control of bacterial communities during drinking water production and distribution. This article reviews (i) existing knowledge on biological stability controlling factors and (ii) how these factors are affected by drinking water production and distribution conditions. In addition, (iii) the concept of biological stability is discussed in light of experience with well-established and new analytical methods, enabling high throughput analysis and in-depth characterization of bacterial communities in drinking water. We discussed, how knowledge gained from novel techniques will improve design and monitoring of water treatment and distribution systems in order to maintain good drinking water microbial quality up to consumer’s tap. A new definition and methodological approach for biological stability is proposed.

Simulating Residential Water Demand with a Stochastic End-Use Model

Abstract: A water demand end-use model was developed to predict water demand patterns with a small time scale (1 s) and small spatial scale (residence level). The end-use model is based on statistical inform...

Benefits and challenges of using smart meters for advancing residential water demand modeling and management

Abstract: Over the last two decades, water smart metering programs have been launched in a number of medium to large cities worldwide to nearly continuously monitor water consumption at the single household level. The availability of data at such very high spatial and temporal resolution advanced the ability in characterizing, modeling, and, ultimately, designing user-oriented residential water demand management strategies. Research to date has been focusing on one or more of these aspects but with limited integration between the specialized methodologies developed so far. This manuscript is the first comprehensive review of the literature in this quickly evolving water research domain. The paper contributes a general framework for the classification of residential water demand modeling studies, which allows revising consolidated approaches, describing emerging trends, and identifying potential future developments. In particular, the future challenges posed by growing population demands, constrained sources of water supply and climate change impacts are expected to require more and more integrated procedures for effectively supporting residential water demand modeling and management in several countries across the world. We review high resolution residential water demand modeling studies.We provide a classification of existing technologies and methodologies.We identify current trends, challenges and opportunities for future development.