Combined Artificial Intelligence Approaches Analyzing 1000 Conservative Patients with Back Pain—A Methodological Pathway to Predicting Treatment Efficacy and Diagnostic Groups

Patients with back pain are common and present a challenge in everyday medical practice due to the multitude of possible causes and the individual effects of treatments. Predicting causes and therapy efficien cy with the help of artificial intelligence could improve and simplify the treatment. In an exemplary collective of 1000 conservatively treated back pain patients, it was investigated whether the prediction of therapy efficiency and the underlying diagnosis is possible by combining different artificial intelligence approaches. For this purpose, supervised and unsupervised artificial intelligence methods were analyzed and a methodology for combining the predictions was developed. Supervised AI is suitable for predicting therapy efficiency at the borderline of minimal clinical difference. Non-supervised AI can show patterns in the dataset. We can show that the identification of the underlying diagnostic groups only becomes possible through a combination of different AI approaches and the baseline data. The presented methodology for the combined application of artificial intelligence algorithms shows a transferable path to establish correlations in heterogeneous data sets when individual AI approaches only provide weak results

Enhancing Building Monitoring and Control for District Energy Systems: Technology Selection and Installation within the Living Lab Energy Campus

With regard to climate change, it is imperative to reduce greenhouse gas emissions. Onesolution approach is to increase energy efficiency in buildings. Buildings contribute a high share ofthe total global energy usage. As the rate of new building constructions is low, measures applicableto existing buildings become paramount. Before applying new approaches on a large scale, it isnecessary to evaluate them in a representative, realistic environment. Living labs such as the LivingLab Energy Campus (LLEC) at Forschungszentrum Jülich (FZJ) facilitate innovative monitoring andcontrol approaches in a real-world setting. In this work, we investigate the required steps for bringingsensor and control networks, comprising more than 1800 devices, into 18 existing and new buildings.This enables both room-level monitoring and control, as well as the integration of building-wideautomation. By introducing an ICT infrastructure, we pave the way towards holistic approaches on adistrict level. We describe the workflows used for selected instrumentation variants and show firstinsights from the operation of the resulting infrastructure. We show that the investigated instrumen-tation variants exhibit similar characteristics; however, they affect control behavior differently. Weemphasize that instrumentation should be planned in the context of existing infrastructure. Moreover,we present and evaluate sample measurements obtained from different building

Toward optimal metal-organic frameworks for adsorption chillers : insights from the scale-up of mil-101(cr) and nh 2 -mil-125

The metal–organic frameworks (MOFs) MIL‐101(Cr) and NH2‐MIL‐125 offer high adsorption capacities and have therefore been suggested for sustainable energy conversion in adsorption chillers. Herein, these MOFs are benchmarked to commercial Siogel. The evaluation method combines small‐scale experiments with dynamic modeling of full‐scale adsorption chillers. For the common temperature set 10/30/80 °C, it is found that MIL‐101(Cr) has the highest adsorption capacity, but considerably lower efficiency (−19%) and power density (−66%) than Siogel. NH2‐MIL‐125 increases efficiency by 18% compared with Siogel, but reduces the practically important power density by 28%. From the results, guidelines for MOF development are derived: High efficiencies are achieved by matching the shape of the isotherms to the specific operating temperatures. By only adapting shape, efficiencies are 1.5 times higher. Also, higher power density requires matching the shape of the isotherms to create high driving forces for heat and mass transfer. Second, if MOFs’ heat and mass transfer coefficients could reach the level of Siogel, their maximum power density would double. Thus, development of MOFs should go beyond adsorption capacity, and tune the structure to the application requirements. As a result, MOFs could to serve as optimal adsorbents for sustainable energy conversion

Toward Optimal Metal–Organic Frameworks for Adsorption Chillers: Insights from the Scale-Up of MIL-101(Cr) and NH₂-MIL-125

The metal–organic frameworks (MOFs) MIL-101(Cr) and NH2-MIL-125 offer high adsorption capacities and have therefore been suggested for sustainable energy conversion in adsorption chillers. Herein, these MOFs are benchmarked to commercial Siogel. The evaluation method combines small-scale experiments with dynamic modeling of full-scale adsorption chillers. For the common temperature set 10/30/80 °C, it is found that MIL-101(Cr) has the highest adsorption capacity, but considerably lower efficiency (−19%) and power density (−66%) than Siogel. NH2-MIL-125 increases efficiency by 18% compared with Siogel, but reduces the practically important power density by 28%. From the results, guidelines for MOF development are derived: High efficiencies are achieved by matching the shape of the isotherms to the specific operating temperatures. By only adapting shape, efficiencies are 1.5 times higher. Also, higher power density requires matching the shape of the isotherms to create high driving forces for heat and mass transfer. Second, if MOFs’ heat and mass transfer coefficients could reach the level of Siogel, their maximum power density would double. Thus, development of MOFs should go beyond adsorption capacity, and tune the structure to the application requirements. As a result, MOFs could to serve as optimal adsorbents for sustainable energy conversion.ChemE/Catalysis Engineerin

Heat supply for office buildings: A research journey through different supply levels at the Campus ofForschungszentrum Jülich

With regard to climate change, the reduction of greenhouse gas emissions, e.g. by introducing and extending the use of renewable energy sources, plays a pivotal role. As a part of the “Energiewende”, the share of renewable energy sources in electricity generation increased rapidly so far, however other sectors, such as the heating sector, are lagging behind. In order to achieve the defined greenhouse gas emission reduction targets, corresponding measures have to be taken in all energy sectors. This especially holds true in the heating sector, which accounts for a high share in carbon dioxide emissions. In the heating sector, key challenges include the integration of renewable energies and waste heat in the heat supply as well as the increase of the efficiency in the building sector. To reduce heating demands while still ensuring thermal comfort for the occupants, different measures can be taken, ranging from design to refurbishment and automation. Due to the low rate of new construction and renovation in Germany and the European Union in general, the building stock will dominate the overall energy demand of buildings for the coming decades. Therefore, solutions which can be easily retrofitted in existing buildings are essential. Within the “Living Lab Energy Campus” (LLEC) initiative at Forschungszentrum Jülich (FZJ), these challenges are addressed by developing, demonstrating and evaluating various measures ranging from district level over building level to room level by using the real infrastructure at the campus. On the supply side at district level, the integration of waste heat of a water-cooled high performance computer from the Jülich Supercomputing Center (JSC) into a low temperature district heating network (LTDH) for the supply of heat to surrounding buildings is studied. Since the waste heat is provided at moderate temperature, heat pumps are installed in the connected buildings to raise the temperature of the supplied heat to the required temperature level of the building's heating system. Cloud-based model predictive controllers have been developed for an overall optimal operation of the LTDH, heat pumps, heat storages and heating distribution systems within the buildings. The developed control methods have been tested and evaluated using a digital twin. After start of operation of the LTDH, a scientific evaluation of different control methods as well as of the ICT setup can be conducted. Besides this, the automation system of a heating substation with heat exchanger fed by a traditional district heating network is connected to the ICTplatform and adapted for scientific monitoring and operation. To raise energy efficiency at building level, innovative cloud-based controllers as well as monitoring methods to raise user awarenesswith respect to energy demand are developed. For the evaluation of these methods, several buildings including those connected to the LTDH have been equipped on room level with radio-based sensors, measuring indoor air quality and energy demand related parameters, and actuators, allowing the local and remote control of heating systems, lighting systems and venetian blinds. Occupantscan view sensor data of their room via the web-based graphical user interface “JuControl” and provide setpoints for e.g. temperature control. The implemented setup allows the use as a testbed for a variety of different automation algorithms. The experiments having already been conducted show the opportunity to increase the energy efficiency and reveal interesting insights by data analysis.In addition to run and evaluate single measures separately, the developed ICT infrastructure also enables the combined operation of several measures in parallel across different levels and sectors, e.g. a grid-supporting heat pump operation. Finally, a first evaluation of the wide range of measures including the different characteristics regarding costs, implementation efforts and efficiency gains is shown.The general concept of each measure as well as the developed tools, methods and model libraries for optimal design and operation can be transferred to similar use cases. For wider application, also a release of the developed software elements is planned

Heat supply for office buildings: A research journey through different supply levels at the Campus of Forschungszentrum Jülich

With regard to climate change, the reduction of greenhouse gas emissions, e.g. by introducing and extending the use of renewable energy sources, plays a pivotal role. As a part of the “Energiewende”, the share of renewable energy sources in electricity generation increased rapidly so far, however other sectors, such as the heating sector, are lagging behind. In order to achieve the defined greenhouse gas emission reduction targets, corresponding measures have to be taken in all energy sectors. This especially holds true in the heating sector, which accounts for a high share in carbon dioxide emissions. In the heating sector, key challenges include the integration of renewable energies and waste heat in the heat supply as well as the increase of the efficiency in the building sector. To reduce heating demands while still ensuring thermal comfort for the occupants, different measures can be taken, ranging from design to refurbishment and automation. Due to the low rate of new construction andrenovation in Germany and the European Union in general, the building stock will dominate the overall energy demand of buildings for the coming decades. Therefore, solutions which can be easily retrofitted in existing buildings are essential.Within the “Living Lab Energy Campus” (LLEC) initiative at Forschungszentrum Jülich (FZJ), these challenges are addressed by developing, demonstrating and evaluating various measures ranging from district level over building level to room level by using the real infrastructure at the campus. On the supply side at district level, the integration of waste heat of a water-cooled high performancecomputer from the Jülich Supercomputing Center (JSC) into a low temperature district heating network (LTDH) for the supply of heat to surrounding buildings is studied. Since the waste heat is provided at moderate temperature, heat pumps are installed in the connected buildings to raise the temperature of the supplied heat to the required temperature level of the building's heating system. Cloud-basedmodel predictive controllers have been developed for an overall optimal operation of the LTDH, heat pumps, heat storages and heating distribution systems within the buildings. The developed control methods have been tested and evaluated using a digital twin. After start of operation of the LTDH, a scientific evaluation of different control methods as well as of the ICT setup can be conducted. Besides this, the automation system of a heating substation with heat exchanger fed by a traditional district heating network is connected to the ICTplatform and adapted for scientific monitoring and operation. To raise energy efficiency at building level, innovative cloud-based controllers as well as monitoring methods to raise user awareness with respect to energy demand are developed. For the evaluation of these methods, several buildings including those connected to the LTDH have been equipped on room level with radio-based sensors, measuring indoor air quality and energy demand relatedparameters, and actuators, allowing the local and remote control of heating systems, lighting systems and venetian blinds. Occupants can view sensor data of their room via the web-based graphical user interface “JuControl” and provide setpoints for e.g. temperature control. The implemented setup allows the use as a testbed for a variety of different automation algorithms. The experiments havingalready been conducted show the opportunity to increase the energy efficiency and reveal interesting insights by data analysis. In addition to run and evaluate single measures separately, the developed ICT infrastructure also enables the combined operation of several measures in parallel across different levels and sectors, e.g. a grid-supporting heat pump operation. Finally, a first evaluation of the wide range of measures including the different characteristics regarding costs, implementation efforts and efficiency gains is shown.The general concept of each measure as well as the developed tools, methods and model libraries for optimal design and operation can be transferred to similar use cases. For wider application, also a release of the developed software elements is planned