PURPOSE: The objectives of this review are to summarize the current practices and major recent advances in critical care nutrition and metabolism, review common beliefs that have been contradicted by recent trials, highlight key remaining areas of uncertainty, and suggest recommendations for the top 10 studies/trials to be done in the next 10 years.METHODS: Recent literature was reviewed and developments and knowledge gaps were summarized. The panel identified candidate topics for future trials in critical care nutrition and metabolism. Then, members of the panel rated each one of the topics using a grading system (0-4). Potential studies were ranked on the basis of average score.RESULTS: Recent randomized controlled trials (RCTs) have challenged several concepts, including the notion that energy expenditure must be met universally in all critically ill patients during the acute phase of critical illness, the routine monitoring of gastric residual volume, and the value of immune-modulating nutrition. The optimal protein dose combined with standardized active and passive mobilization during the acute phase and post-acute phase of critical illness were the top ranked studies for the next 10 years. Nutritional assessment, nutritional strategies in critically obese patients, and the effects of continuous versus intermittent enteral nutrition were also among the highest-ranking studies.CONCLUSIONS: Priorities for clinical research in the field of nutritional management of critically ill patients were suggested, with the prospect that different nutritional interventions targeted to the appropriate patient population will be examined for their effect on facilitating recovery and improving survival in adequately powered and properly designed studies, probably in conjunction with physical activity.
The built environment requires energy-flexible buildings to reduce energy peak loads and to maximize the use of (decentralized) renewable energy sources. The challenge is to arrive at smart control strategies that respond to the increasing variations in both the energy demand as well as the variable energy supply. This enables grid integration in existing energy networks with limited capacity and maximises use of decentralized sustainable generation. Buildings can play a key role in the optimization of the grid capacity by applying demand-side management control. To adjust the grid energy demand profile of a building without compromising the user requirements, the building should acquire some energy flexibility capacity. The main ambition of the Brains for Buildings Work Package 2 is to develop smart control strategies that use the operational flexibility of non-residential buildings to minimize energy costs, reduce emissions and avoid spikes in power network load, without compromising comfort levels. To realise this ambition the following key components will be developed within the B4B WP2: (A) Development of open-source HVAC and electric services models, (B) development of energy demand prediction models and (C) development of flexibility management control models. This report describes the developed first two key components, (A) and (B). This report presents different prediction models covering various building components. The models are from three different types: white box models, grey-box models, and black-box models. Each model developed is presented in a different chapter. The chapters start with the goal of the prediction model, followed by the description of the model and the results obtained when applied to a case study. The models developed are two approaches based on white box models (1) White box models based on Modelica libraries for energy prediction of a building and its components and (2) Hybrid predictive digital twin based on white box building models to predict the dynamic energy response of the building and its components. (3) Using CO₂ monitoring data to derive either ventilation flow rate or occupancy. (4) Prediction of the heating demand of a building. (5) Feedforward neural network model to predict the building energy usage and its uncertainty. (6) Prediction of PV solar production. The first model aims to predict the energy use and energy production pattern of different building configurations with open-source software, OpenModelica, and open-source libraries, IBPSA libraries. The white-box model simulation results are used to produce design and control advice for increasing the building energy flexibility. The use of the libraries for making a model has first been tested in a simple residential unit, and now is being tested in a non-residential unit, the Haagse Hogeschool building. The lessons learned show that it is possible to model a building by making use of a combination of libraries, however the development of the model is very time consuming. The test also highlighted the need for defining standard scenarios to test the energy flexibility and the need for a practical visualization if the simulation results are to be used to give advice about potential increase of the energy flexibility. The goal of the hybrid model, which is based on a white based model for the building and systems and a data driven model for user behaviour, is to predict the energy demand and energy supply of a building. The model's application focuses on the use case of the TNO building at Stieltjesweg in Delft during a summer period, with a specific emphasis on cooling demand. Preliminary analysis shows that the monitoring results of the building behaviour is in line with the simulation results. Currently, development is in progress to improve the model predictions by including the solar shading from surrounding buildings, models of automatic shading devices, and model calibration including the energy use of the chiller. The goal of the third model is to derive recent and current ventilation flow rate over time based on monitoring data on CO₂ concentration and occupancy, as well as deriving recent and current occupancy over time, based on monitoring data on CO₂ concentration and ventilation flow rate. The grey-box model used is based on the GEKKO python tool. The model was tested with the data of 6 Windesheim University of Applied Sciences office rooms. The model had low precision deriving the ventilation flow rate, especially at low CO2 concentration rates. The model had a good precision deriving occupancy from CO₂ concentration and ventilation flow rate. Further research is needed to determine if these findings apply in different situations, such as meeting spaces and classrooms. The goal of the fourth chapter is to compare the working of a simplified white box model and black-box model to predict the heating energy use of a building. The aim is to integrate these prediction models in the energy management system of SME buildings. The two models have been tested with data from a residential unit since at the time of the analysis the data of a SME building was not available. The prediction models developed have a low accuracy and in their current form cannot be integrated in an energy management system. In general, black-box model prediction obtained a higher accuracy than the white box model. The goal of the fifth model is to predict the energy use in a building using a black-box model and measure the uncertainty in the prediction. The black-box model is based on a feed-forward neural network. The model has been tested with the data of two buildings: educational and commercial buildings. The strength of the model is in the ensemble prediction and the realization that uncertainty is intrinsically present in the data as an absolute deviation. Using a rolling window technique, the model can predict energy use and uncertainty, incorporating possible building-use changes. The testing in two different cases demonstrates the applicability of the model for different types of buildings. The goal of the sixth and last model developed is to predict the energy production of PV panels in a building with the use of a black-box model. The choice for developing the model of the PV panels is based on the analysis of the main contributors of the peak energy demand and peak energy delivery in the case of the DWA office building. On a fault free test set, the model meets the requirements for a calibrated model according to the FEMP and ASHRAE criteria for the error metrics. According to the IPMVP criteria the model should be improved further. The results of the performance metrics agree in range with values as found in literature. For accurate peak prediction a year of training data is recommended in the given approach without lagged variables. This report presents the results and lessons learned from implementing white-box, grey-box and black-box models to predict energy use and energy production of buildings or of variables directly related to them. Each of the models has its advantages and disadvantages. Further research in this line is needed to develop the potential of this approach.
The increasing share of renewable production like wind and PV poses new challenges to our energy system. The intermittent behavior and lack of controllability on these sources requires flexibility measures like storage and conversion. Production, consumption, transportation, storage and conversion systems become more intertwined. The increasing complexity of the system requires new control strategies to fulfill existing requirements.The SynergyS project addresses the main question how to operate increasingly complex energy systems in a controllable, robust, safe, affordable, and reliable way. Goal of the project is to develop and test a smart control system for a multi-commodity energy system (MCES), with electricity, hydrogen and heat. In scope are an industrial cluster (Chemistry Park Delfzijl) and a residential cluster (Leeuwarden) and their mutual interaction. Results are experimentally tested in two real-life demo-sites scale models: Centre of Expertise Energy (EnTranCe) and The Green Village (TU Delft) represent respectively the industrial and residential cluster.The result will be a market-driven control system to operate a multi-commodity energy system, integrating the industrial and residential cluster. The experimental setup is a combination of physical demo-site assets complemented with (digital) asset models. Experimental validation is based on a demo-scenario including real time data, simulated data and several stress tests.In this session we’ll elaborate more on the project and present (preliminary) results on the testing criteria, scenarios and experimental setup.
LINK
Along with the rapidly growing number of disabled people participating in competitive sports, there is an increased need for (para)medical support in disability sports. Disabled athletes experience differences in body composition, metabolism, training load and habitual activity patterns compared with non-disabled athletes. Moreover, it has been suggested that the well-recognized athlete triad, and low energy availability and low bone mineral density in particular, is even a greater challenge in disabled athletes. Therefore, it is not surprising that sport nutritionists of disabled athletes have expressed an urgency for increased knowledge and insights on the nutritional demands of this group. This project aims to investigate energy expenditure, dietary intake, body composition and bone health of disabled athletes, ultimately leading to nutritional guidelines that promote health and optimal sports performance for this unique population. For this purpose, we will conduct a series of studies and implementation activities that are inter-related and build on the latest insights from sports practice, technology and science. Our international consortium is highly qualified to achieve this goal. It consists of knowledge institutes including world-leading experts in sport and nutrition research, complemented with practical insights from nutritionists working with disabled athletes and the involvement of athletes and teams through the Dutch and Norwegian Olympic committees. The international collaboration, which is a clear strength of this project, is not only focused on research, but also on the optimization of professional practice and educational activities. In this regard, the outcomes of this project will be directly available for practical use by the (para)medical staff working with disabled athletes, and will be extensively communicated to sport teams to ensure that the new insights are directly embedded into daily practice. The project outcomes will also be incorporated in educational activities for dietetics and sport and exercise students, thereby increasing knowledge of future practitioners.
Along with the rapidly growing number of disabled people participating in competitive sports, there is an increased need for (para)medical support in disability sports. Disabled athletes experience differences in body composition, metabolism, training load and habitual activity patterns compared with non-disabled athletes. Moreover, it has been suggested that the well-recognized athlete triad, and low energy availability and low bone mineral density in particular, is even a greater challenge in disabled athletes. Therefore, it is not surprising that sport nutritionists of disabled athletes have expressed an urgency for increased knowledge and insights on the nutritional demands of this group. This project aims to investigate energy expenditure, dietary intake, body composition and bone health of disabled athletes, ultimately leading to nutritional guidelines that promote health and optimal sports performance for this unique population. For this purpose, we will conduct a series of studies and implementation activities that are inter-related and build on the latest insights from sports practice, technology and science. Our international consortium is highly qualified to achieve this goal. It consists of knowledge institutes including world-leading experts in sport and nutrition research, complemented with practical insights from nutritionists working with disabled athletes and the involvement of athletes and teams through the Dutch and Norwegian Olympic committees. The international collaboration, which is a clear strength of this project, is not only focused on research, but also on the optimization of professional practice and educational activities. In this regard, the outcomes of this project will be directly available for practical use by the (para)medical staff working with disabled athletes, and will be extensively communicated to sport teams to ensure that the new insights are directly embedded into daily practice. The project outcomes will also be incorporated in educational activities for dietetics and sport and exercise students, thereby increasing knowledge of future practitioners.
