A5073807995- Process Optimization and Integration
- Wastewater Treatment and Nitrogen Removal
- Advanced Control Systems Optimization
- Microbial Metabolic Engineering and Bioproduction
- Biofuel production and bioconversion
- Fault Detection and Control Systems
- Crystallization and Solubility Studies
- Membrane Separation Technologies
- Probabilistic and Robust Engineering Design
- Viral Infectious Diseases and Gene Expression in Insects
- Water Systems and Optimization
- Phase Equilibria and Thermodynamics
- Risk and Safety Analysis
- Catalysis for Biomass Conversion
- Constructed Wetlands for Wastewater Treatment
- Analytical Chemistry and Chromatography
- Water Treatment and Disinfection
- Groundwater flow and contamination studies
- Mineral Processing and Grinding
- Ammonia Synthesis and Nitrogen Reduction
- Advanced Multi-Objective Optimization Algorithms
- Water Quality Monitoring and Analysis
- Computational Drug Discovery Methods
- Environmental Impact and Sustainability
- Urban Stormwater Management Solutions
Technical University of Denmark
2016-2025
Leo Pharma (Denmark)
2022-2023
Ghent University
2001-2019
John Wiley & Sons (United States)
2019
Hudson Institute
2019
Institute for Computer Aided Design
2009-2013
University of Copenhagen
2013
Ghent University Hospital
2010
Middle East Technical University
2004
In this study, the optimal design and operation of an Organic Rankine Cycle (ORC) system driven by solar energy is investigated. A two-tank sensible thermal storage configured to overcome intermittency energy. circulating fluid, also termed as heat transfer fluid (HTF) that connects collector ORC plays a critical role in system. The mass flowrate HTF determines both temperature amount absorbed from collector. simulation-based optimization model developed work. Process simulation performed...
Abstract The uncertainty and sensitivity analysis are evaluated for their usefulness as part of the model‐building within Process Analytical Technology applications. A mechanistic model describing a batch cultivation Streptomyces coelicolor antibiotic production was used case study. input resulting from assumptions propagated using Monte Carlo procedure to estimate output uncertainty. results showed that significant exists in outputs. Moreover biomass, glucose, ammonium base‐consumption were...
Biocatalysis has been attracting increasing interest in recent years. Nevertheless, most studies concerning biocatalysis have carried out using single enzymes (soluble or immobilized). Currently, multiple enzyme mixtures are attractive for the production of many compounds at an industrial level. In this review, a classification multienzyme-catalyzed processes is proposed. Special emphasis placed on description multienzyme ex-vivo systems where several reactions by combination acting outside...
Abstract Significant progress in the area of simultaneous design and control for chemical processes has been achieved various methodologies have put forward to address this issue over last several decades. These methods can be classified two categories (1) controllability indicator‐based frameworks that are capable screening alternative designs, (2) optimization‐based integrate process system design. The major objective is give an up‐to‐date review state‐of‐the‐art challenging control....
The aim of this work is to develop group-contribution(+) (GC(+)) method (combined group-contribution (GC) and atom connectivity index (CI) method) based property models provide reliable estimations environment-related properties organic chemicals together with uncertainties estimated values. For purpose, a systematic methodology for modeling uncertainty analysis used. includes parameter estimation step determine parameters an establish statistical information about the quality estimation,...
This study aims to demonstrate the application of deep learning quantitatively describe long-term full-scale data observed from wastewater treatment plants (WWTPs) perspectives process modeling, analysis, and forecasting modeling. Approximately, 750,000 measurements including influent flow rate, air temperature, ammonium, nitrate, dissolved oxygen, nitrous oxide (N2O) collected for more than a year Avedøre WWTP located in Denmark are utilized develop neural network (DNN) through supervised...
The use of fluctuating renewable energy over a certain threshold may lead to an unmanageable mismatch between the electricity generation and demand profiles threatening grid's stability. In this study, innovative complex storage/conversion system is proposed for cogeneration electricity, cooling, water by integrating liquefied natural gas (LNG) regasification process, organic Rankine cycle, compressed air storage (CAES) system, multi-effect distillation unit. study attempts minimize CO2...
Quantitative structure-property relationships (QSPRs) are important tools to facilitate and accelerate the discovery of compounds with desired properties. While many QSPRs have been developed, they associated various shortcomings such as a lack generalizability modest accuracy. Albeit machine-learning deep-learning techniques integrated into models, another shortcoming has emerged in form transparency interpretability models. In this work, two interpretable graph neural network (GNN) models...
A COMPREHENSIVE MODEL CALIBRATION PROCEDURE FOR ACTIVATED SLUDGE MODELSA methodology for calibration of the activated sludge plant models is proposed on basis consolidated engineering experience and a scientific approach. According to method, definition target(s) plays crucial role in selection steps incorporated this so-called ‘Biomath-Calibration’ protocol. For modelers protocol tries to...Author(s)Peter A. VanrolleghemGüclü InselBritta PetersenGürkan SinDirk De PauwIngmar NopensHuub...
Originally presented at the 1st IWA/WEF Wastewater Treatment Modelling Seminar (WWTmod 2008), this contribution has been updated to also include valuable feedback that was received during Seminar. This paper addresses a number of basic issues concerning modelling nitrite in key processes involved biological wastewater water treatment. To end, we review different model concepts (together with structures and corresponding parameter sets) proposed for such as two-step...
A rigorous methodology is developed that addresses numerical and statistical issues when developing group contribution (GC) based property models such as regression methods, optimization algorithms, performance statistics, outlier treatment, parameter identifiability, uncertainty of the prediction. The evaluated through development a GC method for prediction heat combustion (ΔHco) pure components. results showed robust lead to best statistics estimation. bootstrap found be valid alternative...
This work aims to obtain full-scale N2O emission characteristics translatable into viable control strategies and conduct testing of the proposed concepts. Data a long-term monitoring campaign was first used quantify probe seasonal pattern. Then trends between production/emission process variables/conditions during typical operating cycles were revealed explore dynamic behavior. A multivariate statistical analysis performed find dependency on relevant variables. The results show for time that...
Abstract By critically evaluating previous models, a new mechanistic model is developed to describe simultaneous storage and growth processes occurring in activated sludge systems under aerobic conditions. Identifiability was considered an important criterion during the development since it among others helps increase realiability applicability of models full‐scale WWTPs. A second order proposed for description degradation products famine The successfully calibrated by only using OUR data...
This paper serves as a problem statement of the issues surrounding uncertainty in wastewater treatment modelling. The proposes structure for identifying sources introduced during each step an engineering project concerned with model-based design or optimisation system. It briefly references methods currently used to evaluate prediction accuracy and discusses relevance evaluations model applications. aims raise awareness initiate comprehensive discussion among professionals on issues. also...