dataesr/scientific-paragraphs-categorization huggingface dataset:
Waste Heat Recovery Energy Model 4. 2. 1. OMEGAlpes Optimisation Process Modelling OMEGAlpes energy modelling for the use case of waste heat recovery is performed considering several simplifying hypotheses and is supported by model equations. All those pieces of information, as well as detailed code and results, are available in the related notebook specifically edited for this article (see the Supplementary Materials section). The aim of this section is to present OMEGAlpes modelling principles rather than an exhaustive description of its source code. OMEGAlpes provides to the user the opportunity to integrate all the energy balance equations by using the system of energy units. First, the modelling process consists of defining the energy units corresponding to each energy system. Table  2  shows this modelling association between energy systems and OMEGAlpes energy units.
Notebooks can serve as collaborative objects thanks to their intermediate level of complexity compared to the framework source code or complete documentation. In addition, other notebooks are available to serve as tutorials for the use of the tool. The objective is to provide a library of examples as educational as possible in order to provide a maximum understanding of the modelling possibilities of OMEGAlpes. The case studies have been classified according to two fields: waste heat recovery and energy autonomy, mainly consisting of PV self-consumption. Table  6  presents these case studies with their associated publications and specifications. In the actors column, LNCMI stands for French National Laboratory for High Magnetic Fields, which is an electro-intensive laboratory. The CCIAG is the Grenoble district heating network operator.
One of the main interesting points regarding waste heat recovery lies in its positive impact on energy transitions thanks to reduction of GHG emissions. Waste heat represents an important and underexploited potential low-carbon heat source. However, waste heat recovery brings about many challenges. In the design phase, technical challenges include modelling accuracy of district heating, location, temperature management between source and consumption, and the permanence of the heat potential  [93]. Waste heat recovery projects include many stakeholders such as industry, local authorities, and district heating network operators. These actors' negotiation can have a great influence on the results of the possible energy optimisation. Regarding OMEGAlpes development, an actual waste heat recovery project is under study with the support of the stakeholders, whose presence allows for greater access to data and a better level of technical knowledge.
Conclusions This article presented OMEGAlpes, an open-source model generation tool for districtscale energy systems' preliminary design using MILP optimisation. After reviewing the main characteristics of the energy modelling tool, the article introduced the key features of OMEGAlpes as well as their use in a simplified waste heat recovery example. The range of use cases and associated research fields explored with OMEGAlpes was also presented. OMEGAlpes' open development with the source code documentation and Gitlab, as well as the use cases library, enabled collaborations with laboratories from various fields including electrical engineering, heat, and social sciences. Common work is also lead with engineering schools, engineering offices, local authorities, and energy system operators. These collaborations bring about a connection to the field reality and OMEGAlpes' continuous improvement.
1 kDa for NFU4 and 21. 7 kDa for NFU5 without their predicted MTS. The levels of NFU5 protein produced from the nfu5-2 allele were assessed by semiquantitative protein blot analysis in plants homozygous for the nfu4-2 allele, to rule out signal contribution from NFU4. The NFU5 protein level was $15% less in the nfu4-2 nfu5-2 double mutant compared with WT (Figure  1 , D and Supplemental Figure  S2 ), matching the decrease in NFU5 transcripts (Figure  1, B ). Publicly available RNA-seq data (bar. utoronto. ca) indicated that NFU4 and NFU5 are expressed throughout the plant's life cycle and in all organs. Protein blot analysis using protein extracts from roots, leaves, stems, and reproductive organs confirmed that NFU4 and NFU5 proteins are expressed in all organs, with slightly lower levels in stems and slightly higher levels in flower buds and flowers, based on total protein (Figure  2, A ).
Gene expression analysis Total RNA was extracted using the Plant RNeasy kit (Qiagen), followed by DNase treatment (Turbo DNase kit, Agilent). The integrity of RNA in all samples was verified using agarose gels and RNA purity was analyzed by comparing 260/230 nm and 260/280 nm absorbance ratios (Nanodrop 2000, Thermo Fisher). RNA was quantified using a Qubit 2. 0 fluorometer (Thermo Fisher). RNA (4 mg) was reverse transcribed to cDNA using Superscript III (Thermo Fisher). RT-qPCR reactions were made using SensiFAST master-mix (Bioline), in 20 mL volumes, each with 20 ng of cDNA. Reactions were measured in a Bio-Rad CFX-96 real-time PCR system and cycled as per the Bioline protocol. Data were analyzed using the Bio-Rad CFX Manager 3. 1 software, and were normalized using primer efficiency. Primers are listed in Supplemental Table  S4.
Funding This work was supported by a studentship from the  John Innes Foundation  to A. E. M. ; the  Biotechnology and Biological Sciences Research Council , grant awards  BB/P012523/1  and  BB/P012574/1  to M. F. and J. B; funding from the  T4F Trees for the Future and the Kempe Foundations (GO ¨F)  to O. K. and D. L. ; the  French National Research Agency , grant awards  ANR-13-BSV6-0002-01 ,  ANR-11-LABX-0002-01  ( Lab of Excellence ARBRE ) and  ANR-15-IDEX-04-LUE  ( Lorraine Universited'Excellence)  to N. R. and J. P. -T.
The resulting test cases (TCs) and model solutions are, however, of relevance to any geothermal modelling within the low enthalpy range of conditions. The central goal of our study is to benchmark the capability of different simulators to correctly simulate the individual physical processes relevant to ATES systems (and other low enthalpy geothermal operations). This is a necessary step before simulation of full systems and comparison with operational / field data can be done in a meaningful way. Within the HEATSTORE consortium, seven partners employ 10 different numerical simulators to carry out modelling work (i. e. COM-SOL, MARTHE, ComPASS, Nexus-CSMP++, MOOSE, SEAWATv4, CODE_BRIGHT, Tough3, PFLOTRAN, and Eclipse 100). These simulators cover a range of numerical methods including finite differences, finite volumes, and finite elements, as well as hybridized versions of these.
TC2 results Through this test case, simulators should be able to reproduce typical well test responses based on artificial-yet-representative underground realizations, which include two essential types of heterogeneities: faults and reef structures. Although all participants were able to perform at least one of the variants within TC2, only four (COMPASS, Nexus-CSMP++, MOOSE, and CODE_BRIGHT) were able to carry out all of them. The COMSOL participant chose not to carry out simulations with a Cartesian mesh after not being able to import the mesh information supplied by the guidelines, and for other undisclosed reasons. In the case of MARTHE, the participant reported that the version of the source code used did not allow the simulation of vertical fractures in a radial mesh, and the SEAWATv4 and Tough3 participants reported a similar situation.
Acknowledgements This work was supported by the  HEATSTORE  project. HEATSTORE ( 170153-4401 ) is one of nine projects under the  GEOTHERMICA -ERA NET Cofund  aimed at accelerating the uptake of geothermal energy in Europe. The project is subsidized through the  ERANET cofund GEO-THERMICA  (Project n. 731117) by the  European Commission, RVO  (the Netherlands),  DETEC (Switzerland) ,  FZJ-PtJ (Germany) ,  ADEME (France) ,  EUDP (Denmark) ,  Rannis (Iceland) ,  VEA (Belgium) ,  FRCT (Portugal) , and  MINECO (Spain). More information is available via http ://www. heatstore. eu.
[33]. The total organic carbon (TOC) was measured using a Shimadzu TOC-5000-A system (Shimadzu Corporation, Kyoto, Japan) to estimate the mineralization level of the target molecule at the end of the photocatalytic reaction. The abatement of the target molecule was calculated as: Degradation (%) = CA 0 -CA t CA 0 •100 (2) where CA 0 and CA t were, respectively, the pollutant concentrations at time zero and at time t of the reaction. Also, the pollutant mineralization efficiency was calculated as follows: Mineralization (%) = [TOC 0 ] -[TOC t ] [TOC 0 ] •100 (3) where [TOC 0 ] and [TOC t ] were the concentrations of total organic carbon (mg•L -1 ) of the initial pollutant solution and the concentration measured after an irradiation time t. All photocatalytic investigations were conducted in triplicate and the averages of the collected data were considered.
Structural and Textural Investigations X-ray diffraction is an outstanding investigation method used to highlight the extent of the crystallinity of solid samples and calculate the phase purity, provided by a convenient database of patterns of already-known solids. The XRD patterns of the samples investigated in this work are shown in Figure  2. The XRD patterns indicated the presence of large majorities for the anatase phase and small amounts of rutile in all samples. The detailed assignments of the maxima are presented in Table  1. Materials 2021, 14, x FOR PEER REVIEW 6 of 22 The abatement of the target molecule was calculated as: 𝐷𝑒𝑔𝑟𝑎𝑑𝑎𝑡𝑖𝑜𝑛 (%) = 𝐶𝐴 0 -𝐶𝐴 𝑡 𝐶𝐴 0 • 100 (2) where CA0 and CAt were, respectively, the pollutant concentrations at time zero and at time t of the reaction. Also, the pollutant mineralization efficiency was calculated as follows: 𝑀𝑖𝑛𝑒𝑟𝑎𝑙𝑖𝑧𝑎𝑡𝑖𝑜𝑛 (%) = [𝑇𝑂𝐶 0 ] -[𝑇𝑂𝐶 𝑡 ] [𝑇𝑂𝐶 0 ] • 100 (3) where [ 0 ] and [  ] were the concentrations of total organic carbon (mg L -1 ) of the initial pollutant solution and the concentration measured after an irradiation time.
Structural and Textural Investigations X-ray diffraction is an outstanding investigation method used to highlight the extent of the crystallinity of solid samples and calculate the phase purity, provided by a convenient database of patterns of already-known solids. The XRD patterns of the samples investigated in this work are shown in Figure  2. The XRD patterns indicated the presence of large majorities for the anatase phase and small amounts of rutile in all samples. The detailed assignments of the maxima are presented in Table  1.
E-550 The porous structure of the samples was investigated by using pure nitrogen adsorption at 77 K. The isotherms and the pore size distribution curves are displayed in Figure  4  and the textural data are given in Table  4. The isotherms of the samples E-550 and P-550 could be appointed as type IV according to the IUPAC classification  [37]. This behavior is specific to solids with porous structures that are able to adsorb in multilayers. The loops corresponding to samples E-550 and P-550 could be easily fitted as H2(b) types: the steep part of the desorption branch was attributed to the "ink bottle" pore shape  [29]. The values of the specific surface areas determined by applying the BET equation were, respectively, 38. 08 (E-550) and 43. 63 (P-550) m 2 g -1. The fitting of the BJH pore size distribution model made it possible to define the characteristic diameters for these samples, which were, respectively, 3.
The porous structure of the samples was investigated by using pure nitrogen adsorption at 77 K. The isotherms and the pore size distribution curves are displayed in Figure  4  and the textural data are given in Table  4. The isotherms of the samples E-550 and P-550 could be appointed as type IV according to the IUPAC classification  [37]. This behavior is specific to solids with porous structures that are able to adsorb in multilayers. The loops corresponding to samples E-550 and P-550 could be easily fitted as H2(b) types: the steep part of the desorption branch was attributed to the "ink bottle" pore shape  [29]. The values of the specific surface areas determined by applying the BET equation were, respectively, 38. 08 (E-550) and 43. 63 (P-550) m 2 •g -1. The fitting of the BJH pore size distribution model made it possible to define the characteristic diameters for these samples, which were, respectively, 3.
Furthermore, as shown in Figure  9 , the data found for the photocatalysis with P frameworks indicated very similar behavior. In the case of this system, the hierarchy for mineralization activity was P-750 > P-650 > P-550. Also, in the same figure, it can be seen than the best samples from the E and P series displayed more positive roles in the mineralization of the target molecule than the plain TiO 2 used as a control in our photocatalytic activity investigations. Moreover, for the samples with lower mineralization efficiency, the results suggest that CA reaction intermediates still remained in the treated solutions after 180 min of reaction. It should be noted that the analysis of the recorded HPLC/DAD chromatograms of the samples collected from the reaction media at different time intervals showed that the photodegradation of the target molecule was certainly conducive to the formation of several reaction intermediates.
The reusability potential of the optimal photocatalyst was also investigated as such an evaluation is essential to in order to check whether a catalyst is suitable for future practical applications. Hence, five successive photocatalytic tests were conducted for 60 min under UV-A irradiation conditions. After each cycle, the catalyst was recovered by filtration, washed, dried and reused in a new photocatalytic test. The obtained results for the cycling stability of E-750 are shown in Figure  10. promising for practical applications. For E-550 and E-650, the calculated mineralization yields were slightly lower (88% and 92%, respectively). Furthermore, as shown in Figure  9 , the data found for the photocatalysis with P frameworks indicated very similar behavior. In the case of this system, the hierarchy for mineralization activity was P-750 > P-650 > P-550.
Also, in the same figure, it can be seen than the best samples from the E and P series displayed more positive roles in the mineralization of the target molecule than the plain TiO2 used as a control in our photocatalytic activity investigations. Moreover, for the samples with lower mineralization efficiency, the results suggest that CA reaction intermediates still remained in the treated solutions after 180 min of reaction. It should be noted that the analysis of the recorded HPLC/DAD chromatograms of the samples collected from the reaction media at different time intervals showed that the photodegradation of the target molecule was certainly conducive to the formation of several reaction intermediates. The main ones detected were 4-chlorophenol and isobutyric acid, which were identified by comparing their characteristic retention times with those found during the analysis of a standard solution of each molecule (data not shown).
However, their formation only occurred up to a certain reaction time and after that they remained in the treated solutions but a reduction in their peak area was observed because of their possible transformation or mineralization. In addition, the data presented in Figure  8  show that the CA was completely oxidized after 60 min of reaction for the sample (E-750 system) showing the best photoactivity. Furthermore, the high value achieved for TOC removal in the presence of the same sample after a reaction time of 180 min clearly confirms the almost total mineralization of the organic reaction intermediates. The reusability potential of the optimal photocatalyst was also investigated as such an evaluation is essential to in order to check whether a catalyst is suitable for future practical applications.
Inside the HPHE there are 14 heat pipes inserted vertically through the separation flange, which are transporting the heat recovered from the primary agent inside the evaporator to the secondary agent inside the condenser. Inside the condenser there are three steel rings and two steel discs for a better circulation of the secondary agent and a more uniform heating. The condenser, the evaporator and the separation flange are connected using 9 screws and nuts. The constructive details of the components can be viewed in Table  1. The design of the heat pipe heat recovery system was made using the Autodesk Inventor 2018 software. The model and its components can be seen in Figure  2. a high energy efficient innovative waste heat recovery system. The results of the experimental investigations were validated through numerical simulations.
Inside the condenser there are three steel rings and two steel discs for a better circulation of the secondary agent and a more uniform heating. The condenser, the evaporator and the separation flange are connected using 9 screws and nuts. The constructive details of the components can be viewed in Table  1. The design of the heat pipe heat recovery system was made using the Autodesk Inventor 2018 software. The model and its components can be seen in Figure  2.
Numerical Simulations The 3D model designed in the Autodesk Inventor environment was imported in Autodesk CFD Simulation software. The geometry was discretized in a network consisting 500,000 nodes and the first simulation was run. In order to find a proper mesh that presents the most accurate results, the number of meshing elements was increased gradually until the differences between two consecutive simulations were insignificant. Another criteria for choosing the proper number of mesh elements was the computational power. The higher the number of elements, the longer time required for calculation. According to these criteria, the optimum mesh network was chosen the one consisting in 1. 2 M nodes. The boundary conditions can be observed in Table  2. There were carried out 9 simulations with various parameters.
The temperature of the secondary agent, T Co,1 , and the volume flow rate of the primary agent, q 2 , were kept constant at 10 • C respectively 24 L/min, while the temperature of the primary agent, T Ev,1 , was varied to 60 • C, 65 • C and 70 • C and the volume flow rate of the secondary agent, q 1 , was varied to 1 L/min, 2 L/min and 3 L/min. The simulations were run in steady state and the results obtained are defining the moment when the temperature at the outlet of the secondary agent reaches a quasiconstant temperature. The governing equations for fluid flow and heat transfer are the Navier-Stokes or momentum equations and the First Law of Thermodynamics or energy equation. These equations are used by the Autodesk CFD Simulation software to calculate and describe the heat transfer process.
Conclusions A heat pipe heat recovery system was designed, manufactured and tested. The thermal performance of the equipment was investigated through experimental tests and confirmed by numerical simulations. Also, an efficiency calculation was made based on the experimental data obtained. Compared with classic heat recovery system, this equipment produces hot water at lower costs, given the fact that the heat pipes are a passive technology and do not require any moving parts. The results showed that it needs about 10-15 min until it is able to produce hot water at almost constant temperature. The efficiency of the heat pipes is increasing directly proportional to the temperature of the primary agent. An efficiency of 76. 7% was obtained with a temperature of 70 °C of the primary heat source, but the results showed that this percentage can be further improved.
Conclusions A heat pipe heat recovery system was designed, manufactured and tested. The thermal performance of the equipment was investigated through experimental tests and confirmed by numerical simulations. Also, an efficiency calculation was made based on the experimental data obtained. Compared with classic heat recovery system, this equipment produces hot water at lower costs, given the fact that the heat pipes are a passive technology and do not require any moving parts. The results showed that it needs about 10-15 min until it is able to produce hot water at almost constant temperature. The efficiency of the heat pipes is increasing directly proportional to the temperature of the primary agent. An efficiency of 76. 7% was obtained with a temperature of 70 • C of the primary heat source, but the results showed that this percentage can be further improved.
Advanced statistical tools are used for analyzing the datasets for signal detection of gradual and abrupt changes, for attribution to specific forcing factors, and for dynamically interpolating between observations for assessing the changing state of the ocean  (71, 72). Vulnerabilities of organisms and ecosystems are studied through laboratory and in situ experiments. The probability that temporary extreme events with severe impacts will occur in the future is explored by analyzing, among others, climate projection ensembles of Earth system model simulations. Special consideration is given to compound events, where conditions are extreme in multiple parameters  (73, 74) , and hybrid events, where the extreme impact arises from a combination of several parameters that, in themselves, are not extreme  (75).
Identifying hotspots of high-impact tipping points in huge datasets may, at times, resemble finding needles in haystacks. A respective operational monitoring requires an intensive flow of high-quality data of diagnostics of the key mechanisms of the coupled Earth system. The data required are preferably provided in near real time to allow user interaction for data quality improvements  (76). Another goal would be to identify important forecast failures and the reasons for them (e. g. , ref. 77 ) through an approach following the "discovery-invention cycle" advocated by ref. 78. Current activities that point in this direction are, for example, the Seamless Global Data Processing and Forecasting System development in ref. 79  (see Goal 2 on their p. 18), and the Copernicus Program by the European Union (see https:// www.
Acknowledgments This work has received funding from the  European Union 's  Horizon 2020 research and innovation programme  under grant agreement  820989  (Project  COMFORT-Our common future ocean  in the Earth system -quantifying coupled cycles of carbon, oxygen, and nutrients for determining and achieving safe operating spaces with respect to tipping points) and the  Bjerknes Centre for Climate Research  strategic project  SKD-LOES  (Senter for klimadynamikk, Low and Overshot Emission Scenariosfrom a high to a low carbon society). F. J. acknowledges funding by the  Swiss National Science Foundation  (Grant  200020_172476 ). We thank  Val Byfield  ( National Oceanography Centre, United Kingdom ) for the permission to use and adapt the conveyor belt circulation figure. The contents of this article reflect only the authors' views-the  European Commission  and their executive agencies are not responsible for any use that may be made of the information it contains.
Conclusion and policy implications Our findings from estimating country-specific multivariate econometric models for eight EU countries over the period of 2007 to 2017 suggest that the changes in the MEPS and the energy labels entering into force in 2010 and 2011 increased the sales share of cold appliances with an energy label of A+ and better between about 15 and 38 percentage points. At the same time, these policies are estimated to have lowered the share of cold appliances labelled A between about 12 and 33 percentage points. Because the changes in the regulation for MEPS and energy labels came into effect around the same time, our empirical analysis does not allow disentangling the contribution of the MEPS and energy labels on the cold market transformation. Qualitatively, these results generally support earlier empirical analyses which employed databases and methodologies different from ours and found MEPS and energy labels to be effective.