Momentum scale calibration of the LHCb spectrometer

For accurate determination of particle masses accurate knowledge of the momentum scale of the detectors is crucial. The procedure used to calibrate the momentum scale of the LHCb spectrometer is described and illustrated using the performance obtained with an integrated luminosity of 1.6 fb-1 collected during 2016 in pp running. The procedure uses large samples of J/ψ → μ + μ - and B+ → J/ψ K + decays and leads to a relative accuracy of 3 × 10-4 on the momentum scale

Power Transformer Fault Diagnosis Using Neural Network Optimization Techniques

Artificial Intelligence (AI) techniques are considered the most advanced approaches for diagnosing faults in power transformers. Dissolved Gas Analysis (DGA) is the conventional approach widely adopted for diagnosing incipient faults in power transformers. The IEC-599 standard Ratio Method is an accurate method that evaluates the DGA. All the classical approaches have limitations because they cannot diagnose all faults accurately. Precisely diagnosing defects in power transformers is a significant challenge due to their extensive quantity and dispersed placement within the power network. To deal with this concern and to improve the reliability and precision of fault diagnosis, different Artificial Intelligence techniques are presented. In this manuscript, an artificial neural network (ANN) is implemented to enhance the accuracy of the Rogers Ratio Method. On the other hand, it should be noted that the complexity of an ANN demands a large amount of storage and computing power. In order to address this issue, an optimization technique is implemented with the objective of maximizing the accuracy and minimizing the architectural complexity of an ANN. All the procedures are simulated using the MATLAB R2023a software. Firstly, the authors choose the most effective classification model by automatically training five classifiers in the Classification Learner app (CLA). After selecting the artificial neural network (ANN) as the sufficient classification model, we trained 30 ANNs with different parameters and determined the 5 models with the best accuracy. We then tested these five ANNs using the Experiment Manager app and ultimately selected the ANN with the best performance. The network structure is determined to consist of three layers, taking into consideration both diagnostic accuracy and computing efficiency. Ultimately, a (100-50-5) layered ANN was selected to optimize its hyperparameters. As a result, following the implementation of the optimization techniques, the suggested ANN exhibited a high level of accuracy, up to 90.7%. The conclusion of the proposed model indicates that the optimization of hyperparameters and the increase in the number of data samples enhance the accuracy while minimizing the complexity of the ANN. The optimized ANN is simulated and tested in MATLAB R2023a—Deep Network Designer, resulting in an accuracy of almost 90%. Moreover, compared to the Rogers Ratio Method, which exhibits an accuracy rate of just 63.3%, this approach successfully addresses the constraints associated with the conventional Rogers Ratio Method. So, the ANN has evolved a supremacy diagnostic method in the realm of power transformer fault diagnosis

Impact of Lithium Battery Recycling and Second-Life Application on Minimizing Environmental Waste

In the prospect of greener transportation means and global emission limitations for the protection of the environment, the electric vehicles’ market share is constantly increasing. It is expected that 32% of new vehicles sold in 2030 will be pure electric or plug-in hybrids. As all electric vehicles utilize lithium batteries to power the powertrain, the need for rare earth materials, like lithium or nickel, exceeds the planet’s ability to provide the required capacities. Additionally, even though lithium-ion batteries provide high energy density, they have some disadvantages like a limited range and durability at high-temperature operation. This issue can be improved greatly with the implementation of a hybrid energy storage system consisting of batteries and ultracapacitors. In this paper, the power efficiency of this storage system will be analyzed. Finally, when the cells reach below a specific capacity threshold, they can be removed from the vehicle to be installed in renewable energy plants for storing surplus energy production. Therefore, environmental waste is minimized while simultaneously assisting grid power demands, before being recycled to recover a portion of the rare metals used

Advanced Manufacturing Design of an Emergency Mechanical Ventilator via 3D Printing—Effective Crisis Response

Nowadays, there is a market need that is pushing manufacturers to support more sustainable product designs regardless of any crisis. Two important lessons that society inferred from the COVID-19 pandemic are that the industry needs an improved collaboration efficiency that can handle such emergencies and improve its resource conservation to avoid having shortages. Additive manufacturing technologies use 3D object scanners to direct hardware to deposit material, layer upon layer, in precise geometric shapes, and are positioned to provide a disruptive transformation in how products are designed and manufactured. They can provide for the planet in fighting against crisis from a materials and applications perspective. In this context, the optimization and production of emergency ventilators in health systems were investigated with plans for 3D printing received from the University of Illinois Urbana–Champaign. An evaluation of the printability of CAD files and a partial redesign to limit dimensional variability, acceptable surface finish, and a more efficient printing process were performed. Six parts of the design were redesigned to make printing easier, faster, and less expensive. In the case of the O2 inlet attachment, the necessary supports were difficult to remove due to the part’s geometry, leading to redesign. The modulator top and bottom part, the patient tee, the manometer body, and the pop-off valve cap were also redesigned in order to avoid dimensional variability and possible rough surfaces. Metallic and thermoplastic composite ventilators were produced and then tested in real operating conditions, such as in a hospital setting with a realistic oxygen supply. The preliminary findings are promising compared to the initial design, both in terms of construction quality and performance such as exhalation rate adjustment and emergency valve operation. Also, a combination of manufacturing technologies was evaluated. The modifications allowed optimal casting (injection molding) of the parts and therefore faster production, instead of printing each part, when high output is required

Advanced Manufacturing Design of an Emergency Mechanical Ventilator via 3D Printing—Effective Crisis Response

Nowadays, there is a market need that is pushing manufacturers to support more sustainable product designs regardless of any crisis. Two important lessons that society inferred from the COVID-19 pandemic are that the industry needs an improved collaboration efficiency that can handle such emergencies and improve its resource conservation to avoid having shortages. Additive manufacturing technologies use 3D object scanners to direct hardware to deposit material, layer upon layer, in precise geometric shapes, and are positioned to provide a disruptive transformation in how products are designed and manufactured. They can provide for the planet in fighting against crisis from a materials and applications perspective. In this context, the optimization and production of emergency ventilators in health systems were investigated with plans for 3D printing received from the University of Illinois Urbana–Champaign. An evaluation of the printability of CAD files and a partial redesign to limit dimensional variability, acceptable surface finish, and a more efficient printing process were performed. Six parts of the design were redesigned to make printing easier, faster, and less expensive. In the case of the O2 inlet attachment, the necessary supports were difficult to remove due to the part’s geometry, leading to redesign. The modulator top and bottom part, the patient tee, the manometer body, and the pop-off valve cap were also redesigned in order to avoid dimensional variability and possible rough surfaces. Metallic and thermoplastic composite ventilators were produced and then tested in real operating conditions, such as in a hospital setting with a realistic oxygen supply. The preliminary findings are promising compared to the initial design, both in terms of construction quality and performance such as exhalation rate adjustment and emergency valve operation. Also, a combination of manufacturing technologies was evaluated. The modifications allowed optimal casting (injection molding) of the parts and therefore faster production, instead of printing each part, when high output is required

Assessment of flexibility options in electric power systems based on maturity, environmental impact and barriers using Fuzzy Logic method and Analytic Hierarchy Process

The rapid integration of variable renewable energy sources (vRES) in conjunction with the reduction of coal-fired power plants increase the need for flexibility in electric power systems. In a previous research paper, twenty-three (23) flexibility options were assessed, based on their technical and economic characteristics, using Fuzzy Logic (FL) method and Analytic Hierarchy Process (AHP). Through this research paper the same Flexibility Options (FO) are assessed based on their maturity level, their environmental impact and the technical, economic, social and political/regulatory barriers they encounter in their deployment in Greece, using again FL and AHP methods. Data concerning maturity level and environmental impact are obtained through literature review while data concerning barriers are collected through a survey of energy expert’s opinions. In both methods (FL and AHP), Demand Response from Large Industrial Plants (DRLIP) is ranked 1st among the flexibility options having FSI 0.745 and GPV 0.483 while variable Renewable Energy Power Plants (vRE) and Biogas Power Plants (BGPP) are ranked 2nd and 3rd respectively. On the contrary, Power to Gas (PtG) is ranked 23rd (lowest in rank) using FL method and 22nd using AHP method. The results of the research are very important for the policymakers as they can identify in which sectors (commercial, environmental, technical, economic, social etc.) should take action in order to promote specific flexibility options according to their policy

Search for Bc+→π+μ+μ−B_c^+\to\pi^+\mu^+\mu^- decays and measurement of the branching fraction ratio B(Bc+→ψ(2S)π+)/B(Bc+→J/ψπ+){\cal B}(B_c^+\to\psi(2S)\pi^+)/{\cal B}(B_c^+\to J/\psi \pi^+)

International audienceThe first search for nonresonant $B_c^+\to\pi^+\mu^+\mu^-$ decays is reported. The analysis uses proton-proton collision data collected with the LHCb detector between 2011 and 2018, corresponding to an integrated luminosity of 9 fb$^{-1}$. No evidence for an excess of signal events over background is observed and an upper limit is set on the branching fraction ratio ${\cal B}(B_c^+\to\pi^+\mu^+\mu^-)/{\cal B}(B_c^+\to J/\psi \pi^+) < 2.1\times 10^{-4}$ at $90\%$ confidence level. Additionally, an updated measurement of the ratio of the $B_c^+\to\psi(2S)\pi^+$ and $B_c^+\to J/\psi \pi^+$ branching fractions is reported. The ratio ${\cal B}(B_c^+\to\psi(2S)\pi^+)/{\cal B}(B_c^+\to J/\psi \pi^+)$ is measured to be $0.254\pm 0.018 \pm 0.003 \pm 0.005$, where the first uncertainty is statistical, the second systematic, and the third is due to the uncertainties on the branching fractions of the leptonic $J/\psi$ and $\psi(2S)$ decays. This measurement is the most precise to date and is consistent with previous LHCb results

Probing the nature of the χc1(3872)\chi_{c1}(3872) state using radiative decays

International audienceThe radiative decays $\chi_{c1}(3872)\rightarrow\psi(2S)\gamma$ and $\chi_{c1}(3872)\rightarrow J/\psi\gamma$ are used to probe the~nature of the~$\chi_{c1}(3872)$ state using proton-proton collision data collected with the LHCb detector, corresponding to an~integrated luminosity of~9fb$^{-1}$. Using the~$B^+\rightarrow \chi_{c1}(3872)K^+$decay, the $\chi_{c1}(3872)\rightarrow \psi(2S)\gamma$ process is observed for the first time and the ratio of its partial width to that of the $\chi_{c1}(3872)\rightarrow J/\psi\gamma$ decay is measured to be $$\frac{\Gamma_{\chi_{c1}(3872)\rightarrow \psi(2S)\gamma}} {\Gamma_{\chi_{c1}(3872)\rightarrow J/\psi\gamma}} = 1.67 \pm 0.21 \pm 0.12 \pm0.04 ,$$ where the first uncertainty is statistical, the second systematic and the third is due to the uncertainties on the branching fractions of the $\psi(2S)$ and $J/\psi$ mesons. The measured ratio makes the interpretation of the $\chi_{c1}(3872)$ state as a~pure $D^0\bar{D}^{*0}+\bar{D}^0D^{*0}$ molecule questionable and strongly indicates a sizeable compact charmonium or tetraquark component within the $\chi_{c1}(3872)$ state

Measurement of CP violation in B0→ψ(→ℓ+ℓ−)KS0(→π+π−)B^0\to\psi(\to\ell^+\ell^-)K^0_S(\to\pi^+\pi^-) decays

International audienceA measurement of time-dependent CP violation in the decays of $B^0$ and $\overline{B}^0$ mesons to the final states $J/\psi(\to\mu^+\mu^-)K^0_S$, $\psi(2S)(\to\mu^+\mu^-)K^0_S$ and $J/\psi(\to e^+e^-)K^0_S$ with $K^0_S\to\pi^+\pi^-$ is presented. The data correspond to an integrated luminosity of 6 fb${}^{-1}$ collected at a centre-of-mass energy of $\sqrt{s}=13$ TeV with the LHCb detector. The CP-violation parameters are measured to be \begin{align*} S_{\psi K^0_S} &= 0.717 \pm 0.013 (\text{stat}) \pm 0.008 (\text{syst}), \\ C_{\psi K^0_S} &= 0.008 \pm 0.012 (\text{stat}) \pm 0.003 (\text{syst}). \end{align*} This measurement of $S_{\psi K^0_S}$ represents the most precise single measurement of the CKM angle $\beta$ to date and is more precise than the current world average. In addition, measurements of the CP-violation parameters of the individual channels are reported and a combination with the LHCb Run 1 measurements is performed