Case study of energy recovery in workshops using induction heating systems

International audienceThe aim of this study is to improve the energy efficiency of an industrial process including an induction heating device by recovering fatal losses coming either from inductor Joule losses or from heated pieces after treatment. Software tool based on the pinch method was developed in Modelica language. A specific model for the induction heating device was written, taking into account the temperature dependence of the thermal properties of the heated metal and of the heating efficiency of the induction device. The collected energy can be reused in relay of a boiler inside the process line for heating pickling baths or washing baths or for space heating or domestic hot water production. It can also be converted into electricity (Organic Rankine Cycle, thermoelectricity). In this paper, the authors present case studies realized in a typical steel forging workshop and in a cast iron foundry. They show that direct reuse of the thermal energy has a payback around 3 years. It requires a coil cooling circuit at high temperature (typically 70 to 300 °C). The conversion into electricity is not relevant because of a very long payback

Prognostic indicators and outcomes of hospitalised COVID-19 patients with neurological disease: An individual patient data meta-analysis

BACKGROUND: Neurological COVID-19 disease has been reported widely, but published studies often lack information on neurological outcomes and prognostic risk factors. We aimed to describe the spectrum of neurological disease in hospitalised COVID-19 patients; characterise clinical outcomes; and investigate factors associated with a poor outcome. METHODS: We conducted an individual patient data (IPD) meta-analysis of hospitalised patients with neurological COVID-19 disease, using standard case definitions. We invited authors of studies from the first pandemic wave, plus clinicians in the Global COVID-Neuro Network with unpublished data, to contribute. We analysed features associated with poor outcome (moderate to severe disability or death, 3 to 6 on the modified Rankin Scale) using multivariable models. RESULTS: We included 83 studies (31 unpublished) providing IPD for 1979 patients with COVID-19 and acute new-onset neurological disease. Encephalopathy (978 [49%] patients) and cerebrovascular events (506 [26%]) were the most common diagnoses. Respiratory and systemic symptoms preceded neurological features in 93% of patients; one third developed neurological disease after hospital admission. A poor outcome was more common in patients with cerebrovascular events (76% [95% CI 67-82]), than encephalopathy (54% [42-65]). Intensive care use was high (38% [35-41]) overall, and also greater in the cerebrovascular patients. In the cerebrovascular, but not encephalopathic patients, risk factors for poor outcome included breathlessness on admission and elevated D-dimer. Overall, 30-day mortality was 30% [27-32]. The hazard of death was comparatively lower for patients in the WHO European region. INTERPRETATION: Neurological COVID-19 disease poses a considerable burden in terms of disease outcomes and use of hospital resources from prolonged intensive care and inpatient admission; preliminary data suggest these may differ according to WHO regions and country income levels. The different risk factors for encephalopathy and stroke suggest different disease mechanisms which may be amenable to intervention, especially in those who develop neurological symptoms after hospital admission

Prognostic indicators and outcomes of hospitalised COVID-19 patients with neurological disease: An individual patient data meta-analysis

Background Neurological COVID-19 disease has been reported widely, but published studies often lack information on neurological outcomes and prognostic risk factors. We aimed to describe the spectrum of neurological disease in hospitalised COVID-19 patients; characterise clinical outcomes; and investigate factors associated with a poor outcome. Methods We conducted an individual patient data (IPD) meta-analysis of hospitalised patients with neurological COVID-19 disease, using standard case definitions. We invited authors of studies from the first pandemic wave, plus clinicians in the Global COVID-Neuro Network with unpublished data, to contribute. We analysed features associated with poor outcome (moderate to severe disability or death, 3 to 6 on the modified Rankin Scale) using multivariable models. Results We included 83 studies (31 unpublished) providing IPD for 1979 patients with COVID-19 and acute new-onset neurological disease. Encephalopathy (978 [49%] patients) and cerebrovascular events (506 [26%]) were the most common diagnoses. Respiratory and systemic symptoms preceded neurological features in 93% of patients; one third developed neurological disease after hospital admission. A poor outcome was more common in patients with cerebrovascular events (76% [95% CI 67–82]), than encephalopathy (54% [42–65]). Intensive care use was high (38% [35–41]) overall, and also greater in the cerebrovascular patients. In the cerebrovascular, but not encephalopathic patients, risk factors for poor outcome included breathlessness on admission and elevated D-dimer. Overall, 30-day mortality was 30% [27–32]. The hazard of death was comparatively lower for patients in the WHO European region. Interpretation Neurological COVID-19 disease poses a considerable burden in terms of disease outcomes and use of hospital resources from prolonged intensive care and inpatient admission; preliminary data suggest these may differ according to WHO regions and country income levels. The different risk factors for encephalopathy and stroke suggest different disease mechanisms which may be amenable to intervention, especially in those who develop neurological symptoms after hospital admission

Prognostic indicators and outcomes of hospitalised COVID-19 patients with neurological disease: An individual patient data meta-analysis.

BackgroundNeurological COVID-19 disease has been reported widely, but published studies often lack information on neurological outcomes and prognostic risk factors. We aimed to describe the spectrum of neurological disease in hospitalised COVID-19 patients; characterise clinical outcomes; and investigate factors associated with a poor outcome.MethodsWe conducted an individual patient data (IPD) meta-analysis of hospitalised patients with neurological COVID-19 disease, using standard case definitions. We invited authors of studies from the first pandemic wave, plus clinicians in the Global COVID-Neuro Network with unpublished data, to contribute. We analysed features associated with poor outcome (moderate to severe disability or death, 3 to 6 on the modified Rankin Scale) using multivariable models.ResultsWe included 83 studies (31 unpublished) providing IPD for 1979 patients with COVID-19 and acute new-onset neurological disease. Encephalopathy (978 [49%] patients) and cerebrovascular events (506 [26%]) were the most common diagnoses. Respiratory and systemic symptoms preceded neurological features in 93% of patients; one third developed neurological disease after hospital admission. A poor outcome was more common in patients with cerebrovascular events (76% [95% CI 67-82]), than encephalopathy (54% [42-65]). Intensive care use was high (38% [35-41]) overall, and also greater in the cerebrovascular patients. In the cerebrovascular, but not encephalopathic patients, risk factors for poor outcome included breathlessness on admission and elevated D-dimer. Overall, 30-day mortality was 30% [27-32]. The hazard of death was comparatively lower for patients in the WHO European region.InterpretationNeurological COVID-19 disease poses a considerable burden in terms of disease outcomes and use of hospital resources from prolonged intensive care and inpatient admission; preliminary data suggest these may differ according to WHO regions and country income levels. The different risk factors for encephalopathy and stroke suggest different disease mechanisms which may be amenable to intervention, especially in those who develop neurological symptoms after hospital admission

Coupled NIRT / 3D-DIC for a FEMU identification of the thermo-mechanical behavior of Zr-4 claddings under simulated Reactivity Initiated Accident

International audienceNowadays, full field measurements techniques enable heterogeneous experiments to be performed without the need of averaging assumptions. The richness and the quantity of recording data obtained by these techniques led to the development of robust identification methods, such as the finite element model updating (FEMU) technique. However, it is still difficult to measure both kinematic and thermal full fields at the same location and time since the methods and the devices used to compute them are radically different. Furthermore, it may be complicated to calibrate the temperature measurement system without interfering with the metallurgical state of the sample. The present paper proposes a low-cost procedure that uses the same two CMOS cameras to compute both the 3D-surface kinematic field and the associated thermal field, by stereo-correlation and near infrared thermography, respectively. No interpolation or smoothing operation were finally necessary. INTRODUCTION The Reactivity Initiated Accident (RIA) is a design basis accident that can potentially occur in pressurized water reactors. During such accident, the fuel claddings can be subjected to intense thermo-mechanical loading conditions. Heating rates above 1000°C/s can be observed up to more than 1000°C while claddings are internally pressurized (5-100 bar). Such thermal conditions may have a strong impact on the mechanical properties of the material, especially above 800°C from which an allotropic phase transformation (hcp → bcc) is expected in Zirconium alloys. The present work aims at characterizing the thermo-mechanical behavior of as-fabricated stress relieved annealed Zircaloy-4 claddings under simulated RIA conditions

Innovative Solutions in Induction Heating for Better Energy Efficiency: Presentation of ISIS Project

International audienceThe Energy Climate Package is the EU response to the Global warming Challenge. Induction heating processes can contribute to the energy saving goal: 20 % saving within 2020. European induction manufacturer already propose many efficient solutions at industrial scale. To improve induction devices for an always better energy efficiency, EDF R&D set up a French cooperative project called ISIS with a financial support of the French National Research Agency. Its objective is to promote induction heating as best available technology (BAT) and to develop innovative solutions to increase its efficiency. The ISIS innovations concern the electroheat conversion of induction devices (auto-adaptive multi-coil power supply, low losses coils) and the recovering of fatally lost energy. This paper shows the mid-term results of this project. Firsts control algorithms were successfully tested on a 100 kW 3-coil power supply. A homogenization technique is proposed to model a multi-strand coil. A heat recovery test bench is build and equipped with a PFC control loop to fit with the production fluctuations

Coupled NIRT / 3D-DIC for a FEMU identification of the thermo-mechanical behavior of Zr-4 claddings under simulated Reactivity Initiated Accident

International audienceNowadays, full field measurements techniques enable heterogeneous experiments to be performed without the need of averaging assumptions. The richness and the quantity of recording data obtained by these techniques led to the development of robust identification methods, such as the finite element model updating (FEMU) technique. However, it is still difficult to measure both kinematic and thermal full fields at the same location and time since the methods and the devices used to compute them are radically different. Furthermore, it may be complicated to calibrate the temperature measurement system without interfering with the metallurgical state of the sample. The present paper proposes a low-cost procedure that uses the same two CMOS cameras to compute both the 3D-surface kinematic field and the associated thermal field, by stereo-correlation and near infrared thermography, respectively. No interpolation or smoothing operation were finally necessary. INTRODUCTION The Reactivity Initiated Accident (RIA) is a design basis accident that can potentially occur in pressurized water reactors. During such accident, the fuel claddings can be subjected to intense thermo-mechanical loading conditions. Heating rates above 1000°C/s can be observed up to more than 1000°C while claddings are internally pressurized (5-100 bar). Such thermal conditions may have a strong impact on the mechanical properties of the material, especially above 800°C from which an allotropic phase transformation (hcp → bcc) is expected in Zirconium alloys. The present work aims at characterizing the thermo-mechanical behavior of as-fabricated stress relieved annealed Zircaloy-4 claddings under simulated RIA conditions

Innovative Solutions in Induction Heating for Better Energy Efficiency: Presentation of ISIS Project

International audienceThe Energy Climate Package is the EU response to the Global warming Challenge. Induction heating processes can contribute to the energy saving goal: 20 % saving within 2020. European induction manufacturer already propose many efficient solutions at industrial scale. To improve induction devices for an always better energy efficiency, EDF R&D set up a French cooperative project called ISIS with a financial support of the French National Research Agency. Its objective is to promote induction heating as best available technology (BAT) and to develop innovative solutions to increase its efficiency. The ISIS innovations concern the electroheat conversion of induction devices (auto-adaptive multi-coil power supply, low losses coils) and the recovering of fatally lost energy. This paper shows the mid-term results of this project. Firsts control algorithms were successfully tested on a 100 kW 3-coil power supply. A homogenization technique is proposed to model a multi-strand coil. A heat recovery test bench is build and equipped with a PFC control loop to fit with the production fluctuations

Coupled NIRT / 3D-DIC for a FEMU identification of the thermo-mechanical behavior of Zr-4 claddings under simulated Reactivity Initiated Accident

International audienceNowadays, full field measurements techniques enable heterogeneous experiments to be performed without the need of averaging assumptions. The richness and the quantity of recording data obtained by these techniques led to the development of robust identification methods, such as the finite element model updating (FEMU) technique. However, it is still difficult to measure both kinematic and thermal full fields at the same location and time since the methods and the devices used to compute them are radically different. Furthermore, it may be complicated to calibrate the temperature measurement system without interfering with the metallurgical state of the sample. The present paper proposes a low-cost procedure that uses the same two CMOS cameras to compute both the 3D-surface kinematic field and the associated thermal field, by stereo-correlation and near infrared thermography, respectively. No interpolation or smoothing operation were finally necessary. INTRODUCTION The Reactivity Initiated Accident (RIA) is a design basis accident that can potentially occur in pressurized water reactors. During such accident, the fuel claddings can be subjected to intense thermo-mechanical loading conditions. Heating rates above 1000°C/s can be observed up to more than 1000°C while claddings are internally pressurized (5-100 bar). Such thermal conditions may have a strong impact on the mechanical properties of the material, especially above 800°C from which an allotropic phase transformation (hcp → bcc) is expected in Zirconium alloys. The present work aims at characterizing the thermo-mechanical behavior of as-fabricated stress relieved annealed Zircaloy-4 claddings under simulated RIA conditions