Load Characteristics Research Articles

Operation strategy for community integrated energy system considering source–load characteristics based on Stackelberg game

Instability in supply and demand, coupled with conflicting market interests, significantly impacts the operational efficiency, reliability, cost-effectiveness, and environmental sustainability of integrated energy systems. To address this issue, an operation strategy for a community integrated energy system based on Stackelberg game theory is proposed, taking into account the characteristics of supply and load. Initially, a master–slave game model for an integrated energy system is established, with energy marketer acting as leader and energy supplier and load aggregator as followers. To manage the uncertainties of wind and photovoltaic power generation, robust optimization theory is employed to construct models for both the short-term and long-term output errors of wind and photovoltaic power generation. This approach allows for a more detailed analysis of the uncertainty associated with wind and photovoltaic power generation. Subsequently, the uniqueness of the equilibrium in the established Stackelberg game model is proven. Utilizing an improved adaptive differential evolutionary algorithm in conjunction with the CPLEX solver, not only is the optimal solution solved for, but also the efficiency of the solution scheme is significantly enhanced. The simulation results demonstrate that the strategy not only boosts the reliability of the integrated energy system but also achieves a cost saving of 1.11%, an increase in energy supplier profit of 5.16%, and a load aggregator consumer surplus of 19.68%. In scenarios considering errors in wind and photovoltaic predictions, the cost savings reach 16.95%, with energy seller and supplier profits improving by 9.34% and 32.47% respectively, and consumer surplus increasing by 18.81%.

Cooperative In Situ Impregnation of PEG and Au Nanoparticles into Expanded CNT Network Toward Composite Phase Change Fibers with High Storage Capacity and Photothermal Conversion

AbstractPhase change fibers with multifunctionalities are a promising material for thermal management applications, however, it is still challenging to simultaneously give the fiber high energy conversion and storage capacity. Here, a cooperative in situ impregnation strategy is reported, to introduce Au nanoparticles (NPs) and polyethylene glycol (PEG) together into carbon nanotube (CNT) network during the expansion process, resulting in a CNT/Au/PEG composite phase change fiber. The obtained composite fiber have the characteristics of high loading (up to 88.0–98.6%) and uniform distribution of Au NPs, and thus exhibits superior mechanical, electrical, and thermal properties. The presence of Au NPs plays more important role in not only improving the PEG crystallinity and phase change enthalpy, but also enhancing the photothermal conversion efficiency (up to 88.2%). There is also a new feature of precise regulation of the phase change temperatures, e.g., from 9.5 to 20.5 °C for the solidification temperature. More importantly, due to the strong confinement of PEG and Au NPs inside the CNT network, the composite fiber also shows excellent thermal stabilities, including the anti‐leakage behavior and cycling phase change ability.

Allostatic Load Is Associated with Overuse Musculoskeletal Injury during US Marine Corps Officer Candidates School.

Overuse musculoskeletal injuries (MSKIs) remain a significant medical challenge in military personnel undergoing military training courses; a further understanding of the biological process leading to overuse MSKI development and biological signatures for injury risk are warranted. The purpose of this study was to determine the association between overuse MSKI occurrence and physiological characteristics of allostatic load (AL) characterized as maladaptive biological responses to chronic stress measured by wearable devices in US Marine Corps officer candidates during a 10-week training course. Devices recorded energy expenditure (EE), daytime heart rate (HR), sleeping HR, and sleep architecture (time and percent of deep, light, REM sleep, awake time, total sleep). Flux was calculated as the raw or absolute difference in the average value for that day or night and the day or night beforehand. Linear mixed-effect model analysis accounting for cardiorespiratory fitness assessed the association between overuse MSKI occurrence and device metrics (α = 0.05). Sixty-nine participants (23 females) were included. Twenty-one participants (eight females) sustained an overuse MSKI. Overuse MSKI occurrence in male participants was positively associated with daytime HR (β = 5.316, p = 0.008), sleeping HR (β = 2.708, p = 0.032), relative EE (β = 8.968, p = 0.001), absolute flux in relative EE (β = 2.994, p = 0.002), absolute EE (β = 626.830, p = 0.001), and absolute flux in absolute EE (β = 204.062, p = 0.004). Overuse MSKI occurrence in female participants was positively associated with relative EE (β = 5.955, p = 0.026), deep sleep time (β = 0.664, p < 0.001), %deep sleep (β = 12.564, p < 0.001) and negatively associated with absolute flux in sleeping HR (β = -0.660, p = 0.009). Overuse MSKI occurrences were associated with physiological characteristics of AL including chronically elevated HR and EE and greater time in restorative sleep stages, which may serve as biological signatures for overuse MSKI risk.

A Two-Stage Operation Strategy for Energy Storage under Extreme-Heat-with-Low-Wind-Speed Scenarios of a Power System

Changes in weather conditions directly impact the output of wind power, photovoltaic systems, and other forms of uncontrollable power generation. During extreme weather events, the output from wind and photovoltaic sources is typically reduced. In light of this, this paper proposes a two-stage operational strategy for energy storage, under scenarios of extreme-heat-with-low-wind-speed, in power systems. Firstly, historical data on wind and solar power, along with weather characteristics, are collected to analyze the power output during multi-day periods of extreme heat and low wind speed. Then, Monte Carlo simulations are employed to generate multi-day load curves with inherent uncertainties, based on regional load characteristics of the power system. Finally, a two-stage operation strategy for energy storage charging and discharging is established. In the first stage, normal operations are conducted to identify periods of power shortage across various types of loads. In the second stage, based on the identified moments of power shortage from the first stage, charging and discharging constraints are applied to the energy storage systems. The feasibility and effectiveness of this two-stage operational strategy are then validated through simulations, using historical data to generate scenarios of multi-day extreme-heat-and-low-wind-speed conditions.

A cross sectional pilot study utilising STrain Analysis and Mapping of the Plantar Surface (STAMPS) to measure plantar load characteristics within a healthy population

BackgroundNo in-shoe systems, measuring both components of plantar load (plantar pressure and shear stress) are available for use in patients with diabetes. The STAMPS (STrain Analysis and Mapping of the Plantar Surface) system utilises digital image correlation (DIC) to determine the strain sustained by a deformable insole, providing a more complete understanding of plantar shear load at the foot-surface interface. Research questionsWhat is the normal range and pattern of strain at the foot-surface interface within a healthy population as measured by the STAMPS system? Is STAMPS a valid tool to measure the effects of plantar load? MethodsA cross-sectional study of healthy participants was undertaken. Healthy adults without foot pathology or diabetes were included. Participants walked 20 steps with the STAMPS insole in a standardised shoe. Participants also walked 10 m with the Novel Pedar® plantar pressure measurement insole within the standardised shoe. Both measurements were repeated three times. Outcomes of interest were global and regional values for peak resultant strain (SMAG) and peak plantar pressure (PPP). ResultsIn 18 participants, median peak SMAG and PPP were 35.01 % and 410.6kPa respectively. The regions of the hallux and heel sustained the highest SMAG (29.31 % (IQR 24.56–31.39) and 20.50 % (IQR 15.59–24.12) respectively) and PPP (344.8kPa (IQR 268.3 – 452.5) and 279.3kPa (IQR 231.3–302.1) respectively). SMAG was moderately correlated with PPP (r= 0.65, p < 0.001). Peak SMAG was located at the hallux in 55.6 % of participants, at the 1st metatarsal head (MTH) in 16.7 %, the heel in 16.7 %, toes 3–5 in 11.1 % and the MTH2 in 5.6 %. SignificanceThe results demonstrate the STAMPS system is a valid tool to measure plantar strain. Further studies are required to investigate the effects of elevated strain and the relationship with diabetic foot ulcer formation.

Guide vane angle and reactor coolant pump performance during idling

In order to study the influence of different guide vane angle variation on performance characteristics of reactor coolant pump (RCP) during idling process, the external characteristics of RCP model with five different guide vane angles at idling process state were analyzed. Radial force characteristics and blade load characteristics of RCP were analyzed. The results show that the head and torque changes of pump with different guide vane angles in different idle period are consistent. The head of DY1model (Guide vane angle increases sharply first and then decreases gently, which convexity is large) is the highest and torque is small. The head drop rate of DY5 model (Guide vane decreases first and then increases, and the concavity is large) is the highest and torque is the largest. With the idling, the radial force of impeller and guide vane decreases gradually. The radial force of DY5 model impeller is small and the fluctuation range is weak. The radial force of DY4 model (Guide vane shows concavity change with gentle increase) impeller before idling is the largest. In the nonlinear transition of idle period, the total radial force of DY4 model is 235 N when idling for 32 s, which is nearly 30 times lower than that before idling, and the radial force decreases the most. In different idling periods, the radial force amplitude of guide vane of DY5 model is the largest, and the radial force decrease amplitude of guide vane of DY4 model is the largest in the whole idling period. The impeller blade load of DY4 and DY5 model pumps with concavity guide vane angle change law is significantly higher than that of other model pumps after the relative position of streamline is 0.6. When the relative position of the guide vane along the streamline direction is less than 0.5, the load fluctuation of the guide vane of each model pump is large. When the relative position is greater than 0.5, the blade load fluctuation is relatively small.

Techno-economic and environmental study of a hybrid solar ground source heat pumps for a heating-dominated community in a cold climate; a case study in Toronto

Employing ground source heat pumps (GSHP) in heating-dominated areas presents challenges, including load imbalance and decreased efficiency. This study examines using solar energy to prevent soil thermal depletion in cold climates by comparing two systems. The first system (HPPV) uses geothermal heat pumps, borehole thermal energy storage, and photovoltaic modules. The second system (ST-HPPV) adds solar thermal collectors to reduce soil thermal depletion over long-term operation. Both systems supply hot or chilled water to the community's fan-coil systems via a short-term storage tank and heat exchanger. Their energy performance, greenhouse gas emissions, and costs were compared with a conventional fossil-fueled system (natural gas boiler and absorption chiller). Results showed the ST-HPPV system outperformed the HPPV system by 15 % in the seasonal coefficient of performance in heating mode after 20 years. However, solar thermal collectors did not benefit the cooling mode due to the community's load characteristics. Cost analysis revealed the HPPV system is more cost effective and reliable due to lower operating and carbon costs. The findings recommend the ST-HPPV system for communities where the annual heating load is 75 % or more of the cooling load.

Experimental study on peak shaving during preheating combustion for different coal ranks: Thermal modification and variable load operation

With the large-scale integration of renewable energy into the power grid, coal-fired power plants shoulder an enormous burden of peak shaving. In this study, the variable load characteristics of different coal ranks were extensively investigated on a 40 kWth down-fired test platform. Moreover, the preheating modification of fuel at ultra-low loads was investigated. A comprehensive evaluation coefficient (Eph) was established to characterize the reactivity of different coal ranks at wide loads. The determination criterion of combustion stability for variable load processes was modified. The results show that the preheating modification of different coal ranks was significant, especially for lower-activity coals such as anthracite and lean coals. The minimum loads after modification were 25 %, 25 %, 35 % and 40 % for ARG (lignite), SM (bituminous), RG (lean coal) and SH (anthracite), respectively. Furthermore, the preheating modification had a positive effect on increasing the variable load rate, which was positively correlated with Eph for different coal ranks. The maximum variable load rates after modification for ARG, SM, RG and SH were 2.78 %/min, 3.13 %/min, 1.79 %/min and 1.15 %/min, which corresponded to the optimum load steps of 25–30 %. The response rate of NO and N2O with time in the low-rank coal is faster than that in the high-rank coal during the variable load process, which is consistent with the trend of the variable load rate. In addition, the conversion of nitrogen oxides decreases and then increases with load, and the inflection points corresponding to AGB, SM, RG and SH are 40 %, 38 %, 70 % and 80 %, respectively. The NOx emissions were less than 335 mg/m3 (@6 % O2) for the different coal ranks during load changes.

A measurement method for zero-degree thermostat

Thermocouple thermometers are widely used in laboratories and industry, the ice-water mixture is usually used as cold end compensation for thermocouple thermometer measurement. However, the ice-water mixture has disadvantages, such as complex manufacturing process, short use time, and unstable internal temperature field. The zero-temperature thermostat can replace the traditional ice water mixture to provide a stable temperature field environment. However, there is no suitable measurement method that can evaluate the zero-degree thermostat to meet the measurement requirements of thermocouple thermometer. Therefore, comparative experiments on temperature deviation, volatility, axial temperature field uniformity, radial temperature field uniformity, and load characteristics of the ice-water mixture and the zero-temperature thermostat are evaluated. In addition, the uncertainty of the zero-temperature thermostat and the ice water mixture is also proposed. The results reveal that the measurement results of temperature deviation, volatility, axial temperature field uniformity and load characteristic of the zero-temperature thermostat is smaller than that of the ice water mixture. Meanwhile, the uncertainty results also reveal that the zero-temperature thermostat is more stable than the ice water mixture. This study provides a comprehensive method for evaluating the performance of zero temperature thermostats, which can be used to verify the accuracy of the instrument and ensures the reliability of the thermocouple thermometers measurement, and promotes the development of zero temperature thermostat in temperature measurement field.

Multi-objective optimization method for medium and long-term power supply and demand balance considering the spatiotemporal correlation of source and load

The medium and long-term supply-demand imbalance of the power system in the context of the new power system is becoming more and more prominent due to the fluctuation and intermittency brought about by the high proportion of new energy sources connected to the grid. In this regard, a multi-objective power supply-demand balance optimization method considering the spatiotemporal correlation of source and load is proposed in this work. First, the autocorrelation and inter-correlation characteristics of source and load are analyzed. On this basis, a multi-dimensional scenario set construction method considering the spatiotemporal correlation of source and load is proposed. Then, the planning capacity of each regional power source and the system operation under each scenario are taken as the optimization variables. Renewable energy electricity curtailment, equivalent annual total cost, and inter-region transmission electricity are taken as the optimization objectives. Various constraints such as power source planning and operation, power balance, inter-region power transmission, and renewable energy power curtailment rate are considered comprehensively. The optimization method for the medium and long-term power supply and demand balance is proposed. Finally, the method is applied to Hunan Province, China to guide power planning. The results show that compared with traditional multi-dimensional correlation scene construction methods, the average probability density functions error of wind turbine output, photovoltaic output, and load constructed in this work decrease by 44.08 %, 73.64 %, and 57.54 %, respectively. It takes into account the regional, temporal, temporal autocorrelation, and inter-correlation of the source and load, and has similar characteristics to historical data. Compared with traditional planning that only considers economy, the optimization plan for power supply and demand balance in this work reduces electricity curtailment and inter-region transmission by 97.04 % and 72.71 %, respectively, balancing renewable energy consumption, economy, and regional independent balancing indicators.

Experimental and theoretical analysis of loading characteristics of electret filter media for charged particles

The degradation of filtration performance in electret filter media during usage poses a significant challenge. Pre-charging of aerosols has been identified as an effective method to mitigate this issue. However, the effects of particle charging characteristics on the loading characteristics of electret filters still need a comprehensive understanding. In this study, a needle-cylinder corona charger was employed to pre-charge aerosols, and the particle charge state was determined by multiphysics simulation. The effects of particle charge polarity and charge quantity on the loading performance of the electret filter were quantitatively investigated. The results showed that the particle charge polarity had a negligible impact on the loading performance under the condition of the equivalent particle charge quantity. In addition, the charged particles effectively improved the efficiency degradation during the loading process of electret media, with higher charge quantities resulting in more pronounced improvements. The electrostatic attenuation factor showed a negative exponential correlation with the particle charge quantity. This was attributed to the uneven particle deposition on fiber surface due to the attraction of charged particles by the opposite charges on the electret fibers, which alleviated the effect of electrostatic shielding.

Research on the minimum network loss optimization control strategy of the active distribution network based on the distributed power flow controller

With large-scale access to distributed new energy, the power flow form of the distribution network tends to be complex. The distribution loop network rate increases, resulting in serious circulation of the distribution network, which places significant pressure on the loss of the distribution network. The problem of network loss change caused by distributed new energy grid connection, coupled with the inconsistency between load fluctuation and output power change of distributed new energy, will have a significant impact on the safety, reliability, and economic operation of the distribution network. Therefore, it is urgent to have good economic and technical means of power flow control. This paper proposes a minimum network loss optimization control strategy for active distribution networks based on a distributed power flow controller. First, according to the characteristics of the distribution network load and the new energy power supply along the distribution line, the multiple sub-modules of the distributed power flow controller are arranged in sections in the distribution loop network line. The regulation effect of the distributed power flow controller on the voltage and power flow of the distribution loop network is analyzed. The loop network current equation and power loss equation after the distributed power flow controller are constructed, and the power equation with the minimum active loss of the active distribution loop network is derived. Second, the control strategy for minimum network loss of the active distribution network based on the distributed power flow controller is proposed. Finally, the simulation model of the active distribution loop network is constructed by PSCAD/EMTDC. The loss of the loop network before and after the distributed power flow controller is simulated and analyzed, and the effectiveness of the proposed strategy is verified.

Characteristics and risk assessment of heavy metals in groundwater at a typical smelter-contaminated site in Southwest China

To explore the characteristics and evaluate the risk of heavy metals in groundwater at a typical smelter-contaminated site, this study focuses on a representative a historical arsenic smelting plant in Southwest China, where the primary historical products were metallic arsenic (∼1000 tons/year) and arsenic trioxide (∼2000 ton/year). The results demonstrated As and Pb as the main pollutants in soil, and As and Cd as main pollutants in groundwater through soil profiling and quarterly groundwater analysis. The maximum As and Pb in the surface soil were 76800 and 2290 mg/kg, respectively, with As vertically infiltrating the deep gravel–sand layer (18–20 m). The groundwater pollution distribution progressively increased along flow direction, influenced by seasonal surface runoff and infiltration fluctuations. The groundwater pollutant concentrations during the dry season notably surpassed those during the wet season, with maximum As and Cd concentrations of 111.64 mg/L and 19.85 μg/L during the dry season, respectively. Furthermore, the analytic hierarchy process (AHP) was applied to evaluate the comprehensive risk of contaminated-site across pollution source load, regional groundwater intrinsic vulnerability, and evaluation of nearby sensitive receptors. The results revealed that the carcinogenic risk of lead in surface soil was moderate to high, while arsenic posed a high carcinogenic risk, contributing to an overall carcinogenic risk proportion of 89.6% in surface soil. Exposure through groundwater intake was identified as the primary pathway, with carcinogenic and noncarcinogenic risks exceeding those through skin contact. The final weights result demonstrated that the principal risk factors are the intrinsic arsenic load and protective target characteristics of regional groundwater at this site. This study provides a reference for comprehensive assessments of similarly contaminated industrial and smelting sites.

Boosting prairie dog optimizer for optimal planning of multiple wind turbine and photovoltaic distributed generators in distribution networks considering different dynamic load models

Deploying distributed generators (DGs) supplied by renewable energy resources poses a significant challenge for efficient power grid operation. The proper sizing and placement of DGs, specifically photovoltaics (PVs) and wind turbines (WTs), remain crucial due to the uncertain characteristics of renewable energy. To overcome these challenges, this study explores an enhanced version of a meta-heuristic technique called the prairie dog optimizer (PDO). The modified prairie dogs optimizer (mPDO) incorporates a novel exploration phase inspired by the slime mold algorithm (SMA) food approach. The mPDO algorithm is proposed to analyze the substantial effects of different dynamic load characteristics on the performance of the distribution networks and the designing of the PV-based and WT-based DGs. The optimization problem incorporates various operational constraints to mitigate energy loss in the distribution networks. Further, the study addresses uncertainties related to the random characteristics of PV and WT power outputs by employing appropriate probability distributions. The mPDO algorithm is evaluated using cec2020 benchmark suit test functions and rigorous statistical analysis to mathematically measure its success rate and efficacy while considering different type of optimization problems. The developed mPDO algorithm is applied to incorporate both PV and WT units, individually and simultaneously, into the IEEE 69-bus distribution network. This is achieved considering residential, commercial, industrial, and mixed time-varying voltage-dependent load demands. The efficacy of the modified algorithm is demonstrated using the standard benchmark functions, and a comparative analysis is conducted with the original PDO and other well-known algorithms, utilizing various statistical metrics. The numerical findings emphasize the significant influence of load type and time-varying generation in DG planning. Moreover, the mPDO algorithm beats the alternatives and improves distributed generators' technical advantages across all examined scenarios.

Study on Activation and Restructuring of Key Strata in Shallowly Buried Coal Seam Bearing Structure and Load Characteristics

The mining of shallow coal seam groups triggers the activation of overlying strata, leading to increased pressure and support difficulties, thereby posing a threat to the safe extraction of underlying coal seams. Against the backdrop of Longhua Coal Mine, this study utilized physical similarity simulation experiments to obtain the activated, restructured load-bearing structure and the migration characteristics of overlying strata. Theoretical calculations were employed to establish both a rolling friction mechanics model for the activated load-bearing structure and a mechanical model for the combined load-bearing structure of key strata. The research indicates that during the initial activation phase, the load-bearing structure exhibits a V-shaped hinged arch, with directly collapsed rock masses transitioning towards spherical shapes, resulting in the sub-key strata shifting from sliding friction to rolling friction. Based on the rolling friction mechanics model of the activated load-bearing structure, we derived the rolling friction coefficient of key blocks in the sub-key strata and the instability criterion of the load-bearing structure under rolling friction conditions. Considering the migration characteristics of the activated restructured load-bearing structure, four types of combined load-bearing structures were identified, and the load calculation formulas in the mechanical model were derived, with the rationality of these formulas verified through case analysis.

Chitosan: A Versatile Biomaterial Revolutionizing Endodontic Therapy.

Owing to their nanoscale dimensions, nanomaterials have special chemical and physical properties that set them apart from their bulk counterparts. The exterior dimensions of a minimum of half of the particles span several nanometers in their size distribution. Silver nanoparticles (AgNPs) are one type of nanomaterial that has been widely used because of their strong antibacterial properties, which can kill bacteria that are resistant to many drugs. Due to its potential for regulated release, localized retention, and safeguarding the active ingredients against environmental or enzymatic deterioration, nanoparticle technology has also emerged as a promising medication delivery method. The techniques for creating nanoparticles can be easily scaled up and used for a wide variety of medications. Since polymeric nanoparticles are biodegradable, biocompatible, and have more readily available formulation techniques than other nanoparticle drug delivery approaches, their range of applications has been expanding. Chitosan, also known as deacetylated polysaccharide, is a straight-chain cationic polymer that is typically a cationic copolymer. It can be generated naturally or by deacetylating chitin. Consequently, it contains an extensive array of biomedical applications, such as efficient healing of wounds, regeneration of tissues, regeneration of bone, and anti-infection. Because of its functional diversity, accessibility, and being both biodegradable and biocompatible, it has a wide spectrum of uses in dentistry. Recent research on chitosan-based nanoparticles is founded on the field's growing comprehension of the characteristics of chitosan and techniques for chemical or physical modification that are used to optimize the drug loading and release characteristics of the nanoparticles.

Restoring force model of phosphogypsum-filled cold-formed thin-walled square steel tube composite wall

The phosphogypsum (PG)-filled cold-formed thin-walled square steel tube (PFCFS) composite wall is a new type of cold-formed steel (CFS) wall. The restoring force model (including the skeleton curve and hysteresis rules) is an important performance of this type of walls. Based on the characteristics of load–displacement curves of the walls, a Pinching4 model for the skeleton curve of the walls is developed. The lateral stiffness and shear capacity of the walls are calculated by theoretical formulas, while other parameters are determined through data fitting. Moreover, the hysteresis rules of the walls adopt the Pivot model, and the Pivot parameters (α and β) of the walls are determined based on the principle of equal energy. Finally, based on the above restoring force model, the energy dissipation analysis for the walls with different parameters was conducted. The results show that improving the PG strength, stud thickness, or reducing the height-width ratio of the walls significantly enhances the energy dissipation capacity of the wall; increasing the OSB thickness, axial force ratio, or reducing the screw spacing gradually improves the energy dissipation capacity of the wall; the OSB configuration and the stud strength have a smaller impact on the energy dissipation of the wall; the energy dissipation capacity of the wall when the hold-down fails is lower.

Impedance analysis of voltage prediction compensation scheme for DC-link oscillation suppression in cascade drive system

The dc-link voltage oscillation caused by the negative impedance characteristic of the constant power load is a significant issue in the series LC branch-permanent magnet synchronous motor (PMSM) cascade system. To this end, this paper proposes a voltage prediction compensation (VPC) strategy to suppress the dc-link voltage oscillation by adding a voltage stability constraint term to the finite control set model predictive current control (FCS-MPCC). First, the linearized q-axis reference voltage is obtained by taking the derivation of the cost function of the VPC, thereby deriving the input impedance of the inverter-permanent magnet motor system. Then, the impedance matching criterion and Nyquist stability criterion are used to theoretically prove that the proposed strategy can effectively improve system stability, and the robustness of the proposed method to changes in motor parameters is analyzed. Finally, experimental verification was conducted on a 1 kW motor platform. The results show that when the motor is running under rated working conditions, after adding the stability constraint, the dc-link voltage fluctuation drops from 40 V to 7 V; the q-axis current pulsation rate also drops to 3.8 %. Theoretical analysis and experimental results show that the VPC strategy can effectively suppress the dc-link voltage oscillation of the cascade drive system.

Optimizing the Support System of a Shallow Buried Tunnel under Unsymmetrical Pressure

In the construction process of tunnel inlet sections, the rock mass can sustain unsymmetrical pressure due to asymmetrical terrain on the two sides of the tunnel. The fact that the inlet sections are usually under shallow buried conditions with strongly weathered rock mass exacerbates the issue. This paper discusses optimization strategies of the initial support of a shallow buried tunnel based on the analytical results of asymmetrical loading characteristics. Numerical simulation is performed with particle flow code (PFC) using the Jianshanji tunnel project as an example. The simulation results show that the bench excavation has slightly less total deformation than the full-section excavation but the deformation range is wider, especially in the tunnel arch. Both lining support and slope reduction treatments can effectively improve rock deformation, with lining support demonstrating better performance in controlling deformation and adjusting stress distribution. Based on the simulation results, the bench excavation and lining support are used in the actual project, and the corresponding optimization control measures were adopted to address deformation issues, including crushed-stone backfilling for compression resistance, advanced grouting reinforcement, and grouting. The field data show that the tunnel stability is effectively improved by adopting the optimization schemes, which further validates the effectiveness of the proposed unsymmetrical control method.

MRI-based pedicle bone quality score: correlation to quantitative computed tomography bone mineral density and its role in quantitative assessment of osteoporosis

BACKGROUND CONTEXTBone quality in the pedicle region generally determines screw pullout strength, insertion torque, and vertebral body loading characteristics. Dual-energy X-ray absorptiometry (DEXA), as the gold standard for evaluating bone mineral density (BMD), cannot measure the BMD of specific parts, such as pedicle, and DEXA is limited in many ways. Recent studies have shown a correlation between the magnetic resonance imaging (MRI)-based vertebral bone quality (VBQ) score and BMD measured using DEXA or quantitative computed tomography (QCT). However, no studies have been reported on the MRI-based pedicle bone quality (PBQ) score. Moreover, few studies have investigated the relationship between MRI-based PBQ and osteoporosis. PURPOSETo create a new site-specific MRI-based PBQ assessment method and assess its diagnostic capacity in patients with normal BMD and osteopenia/osteoporosis. STUDY DESIGN/SETTINGA retrospective study. PATIENT SAMPLEA total of 156 patients underwent lumbar fusion surgery for chronic low back pain at our hospital between 2021 and 2022, with lumbar QCT and T1-weighted MRI performed before surgery. OUTCOME MEASURESCorrelation of the PBQ score with QCT BMD, and the association between the PBQ score and presence of osteopenia/osteoporosis. METHODSBMD of the lumbar was calculated as the mean BMD of the L1 and L2 vertebral bodies on the basis of asynchronous QCT measurements. The PBQ score, which is the average of the bone quality values of both pedicles on the basis of site-specific T1-weighted sagittal MRI images, was calculated by dividing the median signal intensity of the L1–L4 pedicles by the signal intensity of the cerebrospinal fluid at the L3 level. The interobserver reliability of the PBQ score was assessed using the intraclass correlation coefficient (ICC). A receiver operating characteristic curve was drawn, and the area under the curve (AUC) was calculated to assess the predictive performance of PBQ for osteoporosis. The PBQ score was compared with QCT BMD, as the gold standard, using Pearson correlation analysis. RESULTSIn total, 156 patients participated in this study, including 51 in the Normal BMD group and 105 in the osteopenia/osteoporosis group. The PBQ score in the osteopenia/osteoporosis group was significantly higher than that in the normal BMD group (3.19±0.55 vs. 2.84±0.51, p<.001). The VBQ and PBQ scores were calculated by 2 authors and were in good agreement (intraclass correlation coefficient=0.949 and 0.929, respectively). Pearson's test showed a significant negative correlation between PBQ and QCT BMD (r=−0.4887, p<.001). The optimal cutoff PBQ score to differentiate patients with osteopenia/osteoporosis from those with normal BMD was 3.160, with a sensitivity of 66.7%, specificity of 72.5%, and AUC of 0.776. The PBQ score correlated more strongly with QCT BMD (r=−0.4887) than VBQ (r=−0.4078). CONCLUSIONSIn this study, we propose a novel, MRI-based pedicle-specific bone quality score. This is the first study to investigate the relationship between the PBQ score and QCT BMD. The PBQ score showed diagnostic utility, differentiating between patients with osteopenia/osteoporosis and those with normal BMD (AUC=0.776), and the PBQ score correlated more strongly with QCT BMD than VBQ.