Electronic parts in space inevitably subject to radiation effects leading to the degradation of electronic performance or even failure, so radiation performance of an electronic part must be assessed to ensure it work normally in space. At present, to assess the ion radiation effects on a semiconductor device is directly through irradiation tests. However, due to the scarcity of cyclotron resources, the test time is difficult to appoint and the cost is huge. Due to schedule and budget constraints, it is also impossible to conduct irradiation tests on all semiconductor devices in actual space missions. Therefore, assessment of the radiation effects on semiconductor devices through irradiation tests has caused difficulties. Radiation susceptibility of semiconductor device is determined by the design topology and fabrication technology, and the irradiation test data shows that similar semiconductor devices has similar radiation susceptibility, so a method to assess the radiation effects on semiconductor devices base on similarity theory is proposed at first time in this paper. This assessing method does not require irradiation testing and does not require separate sampling. It has the virtues of easy implementation, quick response and low cost, providing an efficient method of assessing radiation effects on semiconductor devices.
This abstract encapsulates an exploration into the innovative potential of harnessing sparks and tungsten electrodes to generate energy akin to nuclear fission. Utilizing a mere 100,000 sparks, powered by just 2 tungsten electrodes and a 500,000-watt supply, this approach yields an impressive 3,121 MeV, signaling a substantial reduction in energy consumption compared to traditional methods. Furthermore, this research proposal reveals the ingenious workings of a machine that employs alternating current (AC) waveforms and an electromagnetic cavity chamber to create a focused electron beam, promising the controlled initiation of nuclear fission reactions with remarkable efficiency. This innovative approach presents an alluring solution to the worldâ\euro™s escalating energy needs, underpinned by a profound understanding of the machineâ\euro™s unique capabilities.
Standard signal processing approaches for scintillation detectors in positron emission tomography (PET) derive accurate estimates for 511 keV photon time of interaction and energy imparted to the detection media from aggregate characteristics of electronic pulse shapes. The ultimate realization of a scintillation detector for PET is one that provides a unique timestamp and position for each detected scintillation photon. Detectors with these capabilities enable advanced concepts for three-dimensional (3D) position and time of interaction estimation with methods that exploit the spatiotemporal arrival time kinetics of individual scintillation photons. In this work, we show that taking into consideration the temporal photon emission density of a scintillator, the channel density of an analog silicon photomultiplier (SiPM) array, and employing fast electronic readout with digital signal processing, a detector that counts and timestamps scintillation photons can be realized. To demonstrate this approach, a prototype detector was constructed, comprising multichannel electronic readout for a bismuth germanate (BGO) scintillator coupled to a 4x4 SiPM array. In proof-of-concept measurements with this detector configuration, we are able to count and provide a timestamp for all optical photons produced by 511 keV photoelectric interactions. We show that this photon counting detector concept can implement 3D positioning of 511 keV photon interactions and thereby enable advanced corrections for time of interaction estimators. We outline the methodology, readout, and approach for achieving this detector capability in first-ever, proof-of-concept measurements for scintillation photon counting detector with analog silicon photomultipliers.
Small modular reactors (SMRs) offer a promising avenue for revolutionizing the traditional role of nuclear plants, transforming them from serving as baseload to flexible con- tributors in both power generation and ancillary services. This paper develops a steady-state model for SMRs, with a focus on incorporating constraints related to â\euro˜xenon poisoningâ\euro™. These constraints are essential to prevent issues during nuclear plant ramp-up following a ramp-down event. These â\euro˜xenon poisoningâ\euro™ constraints have been integrated into a multi-timescale power system operation framework, which also encompasses the formu- lation of inter-temporal coupling constraints. A comprehensive investigation is undertaken to evaluate the impact of integrating SMRs into a power grid with a high penetration of renewable en- ergy, specifically the NREL-118 bus system. A capacity expansion planning analysis is first conducted over multiple years to identify the optimal locations and sizes for deploying SMRs across the network. Additionally, weâ\euro™ve developed various reserve rules that adapt to the ramping status of the SMRs and include different â\euro˜hold-timeâ\euro™ for â\euro˜xenon poisoningâ\euro™ mitigation. Results obtained from a day-long simulation illustrate that the implementation of minimal â\euro˜xenon poisoningâ\euro™ hold-time, coupled with a steady- state guided reserve provision rule, yields the highest revenue â\euro“ approximately 4.14% more than the base case.Â
Contribution: The study discusses the relationship between interpersonal trust and team performance in an exploratory way. The empirical data is collected from students in Electrical Engineering Practice Training Course classes to evaluate their team performance. Background: Interpersonal trust within a team plays a critical role in solving problems and enhancing group performance effectiveness. Research Question: Does interpersonal trust within a team have an impact on team performance? Can interpersonal trust between teammates be improved? Design/Approach: This research presents a case study of 132 electrical engineering university students in China. The students worked in teams completing six simulation experiments in a semester. Findings: The teams always with permanent teammates had the highest level of interpersonal trust and performed the best and the teams always with tentative teammates had the lowest level of trust interpersonal trust and performed worse and worse while the teams whose members were fixed by the instructor increased their interpersonal trust quickly and performed better and better over time. Conclusions: The higher the interpersonal trust within a team, the better the team performance; low initial interpersonal trust within a team can be promoted through intervention.
This letter proposes a method for accurately calculating RF power at a standing wave (SW) transmission line system. It uses two directional couplers and a low-level radio frequency(LLRF) control system. The RF power is calculated from the proposed equations using amplitude and phase measurements of the coupling signals from the two directional couplers. The method is demonstrated adopting two directional couplers with directivity 26 dB and 28 dB respectively at 162.5 MHz over a whole wavelength range. The average power errors observed when using a single directional coupler are about 6.6% and 5.8% respectively, and the calculated power error can be reduced to about 1.0% through the proposed method.
In Positron Emission Tomography (PET) reconstruction, utilizing Time of Flight (TOF) information can significantly enhance the signal-to-noise (SNR) ratio, posing a greater challenge for the precision of TOF. To address this, we employed two distinct waveform datasets for training our developed network. One dataset comprises simulated waveform data obtained through a comprehensive simulation process established using Geant4 and GosSip. The other dataset consists of real waveform data collected from lutetium yttrium orthosilicate (LYSO) scintillators and silicon photomultiplier (SiPM) detectors placed at various positions. Our network, a combination of Transformer and Convolutional Neural Network (CNN), was developed for predicting the TOF of coincidence events based on waveform data from PET detectors. Our network achieved average full width at half maximum (FWHM) of 189 ps, with reductions of 82 ps and 13 ps compared to constant fraction discriminator (CFD) and CNN, across multiple positions. Additionally, there was an average bias reduction of 10.3 ps compared to CNN. We visualized the attention map, revealing the remarkable enhancement of Transformer on the rising edge of waveforms. We also demonstrated the robustness of our proposed network by including waveforms with scattered events in the real training dataset. Data augmentation through translation and flip was investigated and resulted in an improvement of 5 ps. Furthermore, we analyzed the characteristic differences between real and simulated waveform data, providing valuable insights for generating more realistic simulated data in the future. Our network improved the average FWHM and bias, leading to enhanced SNR and clearer imaging. Data augmentation effectively expanded the dataset and facilitated the data collection process.
Maxwell's equations from the 19th century and the almost equally old Lorentz force equation provide the theoretical basis of all of electrical engineering and consequently the foundation for the majority of all modern technologies. For point charges, this system of partial differential equations reduces to the Weber-Maxwell wave equation. In this article, it is shown that this wave equation can be solved analytically for arbitrarily moving point charges, including accelerated charges, and that it is possible to present an analytical solution in the style of Coulomb's law. This finding demonstrates that classical electrodynamics, with all of its numerous wave phenomena, can also be represented without differential equations. This is surprising and unexpected. Moreover, this work enables the development of a novel class of electromagnetic field solvers that are highly superior in terms of speed and quality to existing solvers based on finite-difference time-domain methods, the method of moments, or finite element methods. In the future, this solution will make it possible to simulate any electromagnetic task in interactive form at previously unattainable quality, even on low-performance computers.
The future digitalization of Nuclear power plants (NPP) involves uses of sensors data in digitalize formats and analysis by AI based techniques. The planned and existing network architectures used by U.S. nuclear facilities, particularly in high-security zones near the reactor cores, typically rely on a private intranet that connects multiple computers in a peer-to-peer (P2P) or similar network configuration. These intranets are considered highly secure due to their isolation from the outside world (Internet) and the implementation of data diodes to regulate one-way data flow. Additionally, these facilities employ various security measures, including physical security, authorized access, pre-screened employees, antivirus software, and supply chain verification. While these “air gap” systems and their security frameworks are effective in protecting against traditional threats like malware, ransomware, trojans, and intrusion detection, they may overlook a growing vulnerability related to AI models within these air gap systems. AI models or decision systems utilized within nuclear facilities collect sensor data through the secure network and make critical decisions. However, despite the network’s robust security measures, the threat to AI models posed by adversarial attacks such as troj-AI, evasion-based attacks, backdoor attacks, and pre-trained poisoned attacks is often ignored by conventional virus scanners. These attacks exploit the vulnerabilities of AI models and can be difficult to detect without domain-specific knowledge related to the model data. As the security of nuclear power plants is paramount, it is crucial that we proactively scan and monitor AI models used in different sectors of these facilities. Unfortunately, there is currently no established framework to monitor and scan the behaviors and architectures of AI models, which poses a significant vulnerability for nuclear power plants. To ensure the comprehensive security of nuclear facilities, it is necessary to address this gap by developing specialized frameworks and mechanisms to monitor and assess the security of AI models. These frameworks should be capable of detecting and mitigating adversarial attacks targeting AI models, providing an additional layer of protection alongside existing security measures. By proactively addressing this emerging threat, we can enhance the overall security posture of nuclear power plants and better safeguard against potential risks.
In the first part, uncompensated and unstable polynomials from 2nd order to 10th order are mentioned and it was also concluded that control loops are unstable, the change in coefficients could be seen in the list. In this part, rather taking such unpractical or impractical circuit (or novel B circuit or novel B-topology), a practical ‘buck-boost’ known circuit and its stability has been explored. The known working circuit is assumed as a black box and is declared as equipment under test (EUT) with just input and output and the control loop stability would be investigated using compensators. The author examines the stability and analyses how the abyss of coefficients change with respect to different compensators when the MOSFET switching frequency is changed from 50 Hz to 1.999 MHz or 1999 kHz. Due to large number,this paper studies the abyss of stability and unstability, the game of coefficients, upto third order polynomials. The Bode plots of the compensators designed with P, I, PID, series PI, parallel PI, One pole one zero (1P1Z), multipoles, two pole two zero (2P2Z) and three pole three zero (3P3Z) are submitted. The known theory is also explained as summary. This paper is also the transcript of the proposed invited talk as speaker in some conference.
We investigate an economic readout for depth-of-interaction (DOI) and time-of-flight capable PET detector that consists of an N×N array of crystals whose light outputs at the front- and back-end surfaces are detected by using silicon photomultipliers (SiPM). The N×N SiPMs at the front-end (back-end) of the detector are read by a stripline configured to support discrimination of the row (column) position of the signal-producing crystal, producing only four outputs for the detector. To evaluate this design, we built 4×4 and 8×8 detector modules (DM) by using 3.0×3.0×20 mm3 lutetium-yttrium oxyorthosilicates. The outputs were sampled at 2 GHz and processed offline. For both DMs, crystal discrimination was successful. For the 4×4 (8×8) DM, we obtained a crystal-level energy resolution ranging from 11.3% to 19.3% with an average of 14.1% (9.5% to 21.6% with an average of 13.9%), an average DOI resolution of 2.5 mm (3.1 mm), and a best coincidence resolving time (CRT), measured in coincidence with a single-pixel reference detector with a 302 ps CRT, of 391 ps (603 ps). The CRT deteriorated with the (8×8) DM possibly due to intercrystal scattering.
Recent trends in Positron Emission Tomography (PET) use the time-of-flight (ToF) information in the image reconstruction process to improve the signal-to-noise ratio and the positioning of the annihilation event. One of the components that most contributes to the accuracy of the ToF-PET is the scintillation crystal. The metascintillator approach has been proposed to overcome the time resolution limits of commonly used scintillators. The metascintillator is an engineered composition of small units that combines and optimizes several features in a single scintillator heterostructure. In this work, metascintillator-based brain PET systems were modeled using the GATE Monte Carlo toolkit and compared with designs based on bulk LYSO or BGO. Sensitivity, noise equivalent count rate and scatter fraction were evaluated following the NEMA guidelines. Only data in the list mode format was used for comparison purposes to avoid dependence on the image reconstruction algorithm. To achieve the same peak sensitivity of a system based on a 15 mm thick bulk BGO, the metascintillator-based scanners using BGO/BaF2 , BGO/EJ232, LYSO/BaF2 and LYSO/EJ232 must have thicknesses of 23.2 mm, 22.5 mm, 29.7 mm and 31.1 mm, respectively. The objective of this work is to determine the clinical value of using metascintillator-based detectors in brain PET.
This is a two-part series paper. In this first part of the novel paper, nine uncompensated transfer functions from second (2nd) order upto tenth (10th) order of a solar boost converter which boosts 25V of 255W solar panel to upto 350VDC. The aim of the study is to see what changes in coefficients of polynomials happen from second (2nd) order upto tenth (10th) when the switching frequency is changed from 100 kHz to 1.999 MHz or 1999 kHz. The aim of this paper is transfer functions, not circuits. The graphs/plots showing the voltages level achieved during the change of MOSFET switching frequency from 100 kHz to 1.999 MHz are submitted. The results are used in designing compensator and improving patent - novel B, which is explored in Part-II.
This paper presents the study on known algebraic cubic curves and elliptic curves. This paper derives the popular cubic curve or elliptic curve equation from Weierstrass equation from basic scratch, and discusses various cubic curves, elliptic curves and hyperelliptic curves. Various forms of elliptic curves and cubic algebriac curves viz., Ochoa curve, Mordell curve, projection, birational transformation, Conchoid of de Sluze, Maltese cross curve, Semicubical Parabola, Tschirnhausen Cubic, Right Strophoid, Strophoid, are studied.
In this paper, the comparsion between pulse width modulation(PWM), Direct Memory Access(DMA), power supply and current consumption by peripherals and core in five processors viz., SAMD21G18A, TMS570LS0432, AM3352BZCED60, AM1808EZCE and XCZU3EG-1SBVA484E is studied from designing point of view in applications where power generation, power consumption and autonomy is critical. The contrast has been drawn from datasheets, reference manual and minor calculations and is basically a synopsis.
This work presents the analysis of short-circuit at solar power plant along with calculations,in three part series. The solar power plant is privately owned with rated capacity of 415 kW capable to produce minimum of 880 kWh , providing electricity to six consumers hospital, market/business center, industrial facility, two sectors comprising 400 households and to the Govt. owned 1 MVA, 11kV/400V, Dyn11 distribution transformer. In this study, twelve faults at certain conditions which bypass protectionary switch gear and trigger short circuit in the plant, as per electrical NEC standards is modeled with practical real-world operating conditions, has been analyzed. The failure of protectionary circuit from faults resulting in complete destruction of the solar plant but the successful protection of the DISCOM substation has been analyzed and presented with parameters. In this study, all the faults excluding the faults due to faulty battery management has been collectively presented which trigger uncontrolled short-circuit. The faults have been deliberately induced in the normal operating conditions and twelve such faults at consumer and grid site have been analyzed.