esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Improved MPC-Based Trajectory Tracking Controller Design
### Improved MPC Trajectory Tracking Control Law for the BSR  
Setting an appropriate optimization objective is the key to tracking the desired trajectory as accurately as possible. According to the traditional MPC algorithm, the cost function in this study is designed, as follows:  
\[\min\quad J=\sum_{j=1}^{N}\widetilde{\mathbf{x}}^{T}(k+j)Q\widetilde{\mathbf{ x}}(k+j)+\widetilde{\mathbf{\tau}}^{T}(k+j-1)R\widetilde{\mathbf{\tau}}(k+j-1) \tag{17}\]  
where, \(Q\) and \(R\) are the weighting matrices, and \(N\) is the prediction horizon. The optimization objective of this function is the control input \(\tau\), which is unable to avoid a sudden increment of the control input and it will affect the continuity of the control input.  
Equation (18) is transformed, as follows:  
\[\boldsymbol{\xi}(k)=\left[\begin{array}{c}\widetilde{\mathbf{x}}(k)\\ \widetilde{\mathbf{\tau}}(k-1)\end{array}\right] \tag{18}\]  
A new state-space expression is obtained:  
\[\boldsymbol{\xi}(k+1) =\mathbf{A}\boldsymbol{\xi}(k)+\mathbf{B}\Delta\mathbf{\tau}(k) \tag{19}\] \[\boldsymbol{\eta}(k) =\mathbf{C}\boldsymbol{\xi}(k)\]  
where,  
\[\mathbf{A}=\left[\begin{array}{cc}\widetilde{\mathbf{A}}&\widetilde{ \mathbf{B}}\\ \mathbf{0}_{m\times n}&\mathbf{I}_{m}\end{array}\right] \tag{20}\]  
\[\mathbf{B}=\left[\begin{array}{c}\widetilde{\mathbf{B}}\\ \mathbf{I}_{m}\end{array}\right] \tag{21}\]  
\[\mathbf{C}=\left[\begin{array}{cc}\mathbf{I}_{n}&\mathbf{0}_{n\times m} \end{array}\right] \tag{22}\]  
Here, \(m\) is the dimension of the control input and \(n\) is the dimension of state value.  
In addition, a relaxation factor is designed and added to the objective function in order to avoid no solution. The objective function designed for BSR trajectory tracking control can be established, as follows:  
\[\min\quad\mathbf{J}(k)=\sum_{j=1}^{N_{p}}\left\|\boldsymbol{\eta}(k+j)- \boldsymbol{\eta}_{d}(k+j)\right\|_{Q}^{2}+\sum_{j=1}^{N_{c}}\left\|\Delta \mathbf{\tau}(k+j)\right\|_{R}^{2}+\rho\varepsilon^{2} \tag{23}\]  
where, \(N_{p}\) is the predictive horizon, \(N_{c}\) is the controlling horizon, \(\rho\) is a weighting factor, and \(\varepsilon\) is the relaxation factor.
# Widely-Tunable Ring-Resonator Semiconductor Lasers
## 4 Advanced Designs for Linewidth Reduction
### Utilizing On-Chip High-Q Resonator
A third approach for using the high-\(Q\) resonator to improve laser linewidth is the inclusion of the high-\(Q\) resonator in a drop configuration as an integral part of the laser cavity, as shown in Figure 13a. The inclusion of a third ring resonator inside the cavity increases the cavity loss, and there is a trade-off in the loaded \(Q\) and insertion loss. Simulations show that inclusion of a ring with \(Q\) in the range of ~160 k, results in ~1.9 dB of double-pass loss, which can easily be accounted for with proper design of the gain section. The third ring has a substantially different circumference (>10\(\times\) larger than the Vernier rings used to realize the SWF in our study), as shown in Figure 13b. Rings 1 and 2 are used to filter out a single resonance of ring 3 whose spacing is equal to 25 GHz. Ring 3 is used to filter out a single longitudinal mode of the cavity, whose spacing is a function of the ring \(Q\) and the detuning from ring resonances. Simulations show that single-wavelength operation is straightforward to achieve, as the cavity length enhancement that increases with ring quality factor is compensated by the reduction of 3 dB linewidth of the resonator. Furthermore, the phase of only one cavity has to be optimized for best performance, which simplifies laser operation. There are two disadvantages of this approach: first is that the theoretical linewidth improvement is the smallest between the three considered configurations, owing to the fact that the loaded \(Q\) is the lowest, and the second is a potential limitation due to non-linear effects at high intra-cavity intensities. The latter can be suppressed to a certain degree by utilizing rib type waveguides, or using SiN for waveguides. Figure 12: (**a**) Schematic of external cavity laser with high-\(Q\) ring in all-pass configuration; (**b**) Schematic of external cavity laser with high-\(Q\) ring in add-drop configuration. Figure 13: (**a**) Schematic of laser with high-\(Q\) ring inside the cavity; (**b**) Ring 1 and 2 provide for wide-tunability due to Vernier effect, and filter-out a single resonance of ring 3.
## 2 Control Algorithm
### Robustness Discussion  
Unlike the design concept of conventional SMC, the insensitivity is included in the dynamics model and also guaranteed in our algorithm. In the conventional SMC design, a precise dynamics model is employed and the perturbation is viewed as an extra input. An example is given in Equation (22) in [28]. The change rate of \(s\) is formulated by  
\[\dot{s} = \sigma+M\Delta x+O(\Delta x)^{2}, \tag{29}\]  
and the robustness is discussed based on this formulation. In our approach, however, the perturbations are already included in the parameter \(k\) for \(v_{su}\). Recall that \(k=\bar{F}+\eta\), where \(\bar{F}\) is the bound of the model variation, satisfying \(\hat{f}=\hat{f}+\Delta f\) and  
\[|\Delta f|\leq\bar{F}.\]  
Let \(\hat{\mathbf{X}}=\hat{\mathbf{X}}_{n}+\Delta\mathbf{X}\), where \(\hat{\mathbf{X}}_{n}\) is the nominal states. Then,  
\[\hat{f}(\hat{\mathbf{X}}) = \hat{f}(\hat{\mathbf{X}}_{n}+\Delta\mathbf{X}) \tag{30}\] \[= \hat{f}(\hat{\mathbf{X}}_{n})+\left.\frac{\partial\hat{f}}{ \partial\hat{\mathbf{X}}}\right|_{\hat{\mathbf{X}}_{n}}+\text{H.O.T}\] \[= \hat{f}(\hat{\mathbf{X}})+\Delta f,\]  
where \(\hat{f}(\hat{\mathbf{X}})=\hat{f}(\hat{\mathbf{X}}_{n})\) and \(\Delta f\) includes all the remainder terms. By properly investigating and choosing the bound of \(\Delta f\). The influence of perturbations is included and considered in the control. The advantage of our approach is that the robustness of the control is guaranteed with a proper choice of \(\bar{F}\), and we do not have to worry about specific perturbations. The drawback, of course, it that the control might be inefficient if \(\bar{F}\) is defined too large for the purpose of robustness.
## 1 Introduction
### Contribution  
This paper studies the performance bounds in terms of SE achieved by the 5G-NR precoding matrices in SU-MIMO and MU-MIMO systems. The main contributions of this paper are summarized as follows:  
* A detailed description of the 5G-NR precoding matrices implementation covering both Type I and Type II codebook is provided. Each implementation step outlined in the standard is complemented with the corresponding theoretical explanation to improve its understanding, thus providing a comprehensive guide.
* The SE bounds of the 5G-NR precoding matrices are first obtained for a SU-MIMO scenario by using the Type I codebook. These suboptimal precoding matrices are compared with the optimal singular value decomposition (SVD) solution [5] in order to quantify the margin of improvement that could be attained in future precoding designs. It has been found that an increase in the number of parallel layers does not always imply a higher SE and the best choice has been determined in several configurations.Also, the impact on performance of linear or planar arrays is addressed.
* Then, these results are extended to an MU-MIMO system based on the Type II codebook design. The performance achieved with the standardized solution is compared with the theoretical block-diagonalization ZF method described in [37; 38]. The saturation effect experienced in SE for high SNR values due to interference is exhibited. It is demonstrated how the usage of Type II codebook is limited to users with low spatial correlation.
* The effect of imperfect channel estimation on system performance is numerically evaluated in both cases, single-user and multi-user.
* Moreover, the simulations are performed for several configurations of antenna arrays, number of antenna ports, and parallel data streams. To guarantee a realistic scenario, a clustered delay line (CDL) channel model defined in the 3 GPP technical report (TR) 38-901 is considered.  
Numerical results validate the use of these advanced multi-antenna techniques to reach the demanding SE in 5G/B5G networks. It must be stated that the novelty of the paper relies on a new performance analysis of the SE bounds achieved by the 5G-NR precoding matrices. Additionally, it can be observed the gap between the codebook based standardized solutions and the optimal ones. Furthermore, this article serves as a guide for the practical implementation of precoding strategies which can be very useful for system designers. The obtained results provide relevant insights for the deployment of 5G and beyond networks.
## 4 Quantitative descriptions of scale threshold and scale domain
### Geographic variance method (GVM)  
[PERSON] and [PERSON] [59] proposed the geographic variance method to analyze the scaling effects of geographic phenomena. Geographic variance analysis, which is a hierarchical analysis, can determine the relative variability and independent contribution at each level in a nested hierarchy. Most spatial data can be constructed to a nested hierarchy by a simple aggregation approach, and then the geographic variance method can be applied [30]. According to this theory, the total variability can be divided using the sum of squares at each level, while most geographical phenomena may occur at the level where the level variability is the highest. In other words, the operational scale of a phenomenon coincides with the scale of maximum variability in the data. [PERSON] _et al._[30] argued that the geographic variance method may be a potentially powerful method to detect and describe multi-scale structures of landscapes. However, [PERSON] and [PERSON] [3] thought its validity remains unclear and more analysis is needed. In consequence, this method needs to be further investigated systematically in remote sensing.
# Feasibility of Developing Sustainable Concrete Using Environmentally Friendly Coarse Aggregate
###### Abstract  
Quarry aggregate reserves are depleting rapidly within Australia and the rest of the world due to an increasing demand for aggregates driven by expansion in construction. The annual production of premix concrete in Australia is approximately 30 million cubic meters, while 3-5% of concrete delivered to site remains unused and is disposed of in landfill or crushing plants. The production of coarse aggregates using this waste concrete is potentially a sustainable approach to reduce environmental and economic impact. A testing program has been conducted to investigate mechanical performance and permeation characteristics of concrete produced using a novel manufactured coarse aggregate recycled directly from fresh premix concrete. The recycled coarse aggregate (RCA) concrete satisfied the specified 28-day design strength of 25 MPa and 40 MPa at 28 days and a mean compressive strength of 60 MPa at 90 days. Aggregate grading was observed to determine strength development, while low water absorption, low drying shrinkage, and higher packing density indicate that the RCA concrete is a high-quality material with a dense pore structure. The rough fracture surface of the aggregate increased the bond between C-S-H gel matrix and RCA at the interfacial transition zone. Furthermore, a good correlation was observed between compressive strength and all other mechanical properties displayed by the quarried aggregate concrete. The application of design equations as stated in Australian standards were observed to provide a conservative design for RCA concrete structures based on the mechanical properties.  
aggregate demand; waste concrete; sustainability; mechanical properties; microstructure +
Footnote †: journal: Applied Sciences
## 2 Evaluation Methodology
### DTC Codes  
DTC codes are regulated by the SAE J1979 standard, which is widely recognized within the automotive industry. These codes consist of five characters: one letter (see Table 3) followed by four digits (see Tables 4 and 5). The last two digits specifically indicate the type of failure or error, in accordance with the J1979 standard [50].  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Technology** & **Network Type** & **Spectrum** & **Transmission Range** & **Mobility Support** \\ \hline LoRa [37] & WAN & 433, 868, & 2-5 km (Urban) and & \\ DSRC [38] & Wireless Ad-hoc & 5.8-5.9 GHz & 1 km & Yes \\ C-V2X [39] & Cellular Wireless & 5.9 GHz & \(>\)DSRC and LoRa & Yes \\ Bluetooth [40] & PAN & 2.4 GHz & 100 m (Class 2 device); 1 & Limited \\  & & & (Class 3 device) & \\ WiMAX [41; 42] & Wireless Broadband & 5.8 GHz & 50 km & Yes \\ Zigbee [43] & PAN & 433, 868, & 10–100 m & Yes \\  & & and 915 MHz & & \\ \hline \hline \end{tabular}
\end{table}
Table 2: Comparison of different technologies used in V2X, adapted from Ref [36].  
\begin{table}
\begin{tabular}{c l} \hline \hline
**Character** & **Meaning** \\ \hline P & Power train/engine and transmission \\ B & Bodywork \\ C & Chassis \\ U & Undefined \\ \hline \hline \end{tabular}
\end{table}
Table 3: DTC first character meaning.
## 4 Analysis of On-Site Monitoring Results  
### On-Site Monitoring  
#### 4.1.1 Layout of Monitoring Points  
Considering the specific conditions at the construction site of the existing tunnel, a monitoring plan was meticulously crafted to provide a real-time assessment of the safety status of the existing structures. Given that the existing tunnel was constructed with individual rectangular pipe segments, each measuring 1.5 m in length, and that the joints between these segments experience the most significant variations in stress within the entire system, monitoring points were strategically placed at intervals of 1.5 m along the bottom axis of the existing tunnel's structure and monitored using a hydrostatic level system [44]. Each point of the existing underground pedestrian passages was monitored with hydrostatic level cells, and the readings were taken every day before and after the shield face passing. In total, 64 monitoring points were installed, with 34 points dedicated to Passage A of the rectangular pipe-jacking tunnel and 30 points to Passage B, as depicted in Figure 8.
## 3 Materials and Methods
### D-Loss Software
#### 3.1.6 CO\({}_{2}\) Emissions  
D-Loss makes it easier to calculate and track CO\({}_{2}\) emissions due to ore haulage to the surface. It allows for the estimation of the short- or long-term carbon footprint of stope  
Figure 8: Illustration of the selected stope cross section.  
Figure 7: Example of the selected stopes.  
production. Depending on various rates of dilution, it can easily estimate overall CO\({}_{2}\) emission changes. Since dilution can be controlled by operation and analyzed by software, it will help to understand and reduce overall CO\({}_{2}\) emissions during mining operations.  
In the development stages of this software, the Tier 1 and Tier 2 approaches, developed by the Intergovernmental Panel on Climate Change (IPCC), were considered. Tier 1 considers fuel consumption from national energy statistics and default emission factors, while Tier 2 considers fuel combustion from national energy statistics, together with country-specific emission factors, where possible, derived from national fuel characteristics [30].  
\[\text{Tier 1: CO}_{2}\text{ Emissions = Fuel Consumption }\times\text{Default Emission Factor} \tag{2}\]  
\[\text{Tier 2: CO}_{2}\text{ Emissions = Fuel Consumption }\times\text{Country -- Specific Emission Factor} \tag{3}\]  
The Tier 1 approach was used in the development of D-Loss using the following equations.  
\[\text{Energy Consumption [T]}\text{ = Fuel Consumption [I]}\times\text{Conversion Factor [T]/kt}\times 10^{-3} \tag{4}\]  
\[\text{Carbon Content [Gg C]}\text{ = Carbon emission factor [t C/T]}\times\text{Energy Consumption [T]}\times 10^{-3} \tag{5}\]  
\[\text{Carbon Emission [Gg C]}\text{ = Carbon content [Gg C]}\times\text{Carbon Oxidation Ratio [\%]} \tag{6}\]  
\[\text{CO}_{2}\text{ Emission [Gg CO_{2}]}\text{ = Carbon Emission [Gg C]}\times 44/12 \tag{7}\]  
The user can see the corresponding CO\({}_{2}\) emission amount by changing the dilution and loss percentages on the main page of the interface. Alternatively, the calculation details for the slope selected are available by selecting the \"CO\({}_{2}\) Analysis\" button. The editable parameters are changeable to observe the final CO\({}_{2}\) emission (Figure 9). The diluted tonnage result for the slope is carried here for the selected loss and the dilution percentages for the slope. The estimated CO\({}_{2}\) emission result is also updated on the original page of the interface.  
Figure 9: The output of the CO\({}_{2}\) emission estimation for the selected stopes.
## 3 Results and Discussion
### Analysis of Passivation Properties
A significant decrease in the interface defect density (D\({}_{\rm{it}}\)), could be a cause for the improved passivation after the FGA treatment. An increase in hydrogen activation on both sides of the tunnel oxide interface as well as the nc-SiO\({}_{\rm{x}}\) layer was due to FGA treatment. This led to the best passivation with a 30 nm thick nc-SiO\({}_{\rm{x}}\) layer which was annealed at 950 \({}^{\circ}\)C. The improved results of the passivation characteristics and lower J\({}_{\rm{o}}\) shows that this novel structure would produce a higher efficiency TOPCon cell. Figure 4a depicts microlations in \(\tau_{\rm{eff}}\) and iV\({}_{\rm{oc}}\) following FGA treatment for the 30 nm nc-SiO\({}_{\rm{x}}\) deposited sample. Figure 4b depicts the change in Jafter the FGA at the same parameters as mentioned above. The J\({}_{\rm o}\) was found to be as low as ~1.1 fA/cm\({}^{2}\) after FGA. An improvement was observed at the SiO\({}_{\rm x}\)/nc-SiO\({}_{\rm x}\) passivated contact after thermal annealing at 950 \({}^{\circ}\)C and FGA treatment at 400 \({}^{\circ}\)C, yielding the lowest J\({}_{\rm o}\) and \(\rho\) values. Tunneling efficiency improved as J\({}_{\rm o}\) and \(\rho\) values decreased. Figure 5 depicts the J\({}_{\rm o}\) and \(\rho\) of the deposited samples at a 30 nm thickness of nc-SiO\({}_{\rm x}\) as a function of T\({}_{\rm PDA}\). The amelioration in J\({}_{\rm o}\) and lowest \(\rho\) value for the 30 nm SiO\({}_{\rm x}\)/nc-SiO\({}_{\rm x}\) passivated contact annealed at 950 \({}^{\circ}\)C, was outstanding compared to samples annealed at 850 \({}^{\circ}\)C and 900 \({}^{\circ}\)C. At a 30 nm thickness, the J\({}_{\rm o}\) up to 1.1 fA/cm\({}^{2}\) and \(\rho\) up to 14.7 (m\(\Omega\)/cm\({}^{2}\)) values decreased as the annealing temperature was raised to 950 \({}^{\circ}\)C. After comparing our results with those of other research groups such as [PERSON] et al. [28], it was shown that we attained ameliorated passivation results. To ameliorate the TOPCon solar cell efficiency, nc-SiO\({}_{\rm x}\) was applied in both studies; however, the differences lay with the layer thickness and deposition temperature as well as in the growth method of the SiO\({}_{\rm x}\). The novelty in our results arise from the different treatment steps and fabrication methods employed. Figure 4: (a) Improvement in minority carrier lifetime and implied open-circuit voltage as a function of T\({}_{\rm PDA}\) and FGA. (b) Improvement in rear recombination current density as a function of T\({}_{\rm PDA}\) and FGA. Figure 3: (a) Minority carrier lifetime and implied open-circuit voltage as functions of T\({}_{\rm PDA}\) at 30 nm nc-SiO\({}_{\rm x}\) layer thickness. (b) Recombination current density as a function of T\({}_{\rm PDA}\).
# Fatigue Damage Assessment of Turbine Runner Blades Considering Sediment Wear
## 4 Fatigue Damage Assessment of Turbine Runner Blades
Conversely, when wear is considered, the fatigue damage increases significantly with operation time. Notably, the fatigue damage accumulates gradually under non-flood conditions, but it increases markedly during the flood season. This significant increase is attributed to the structural changes caused by blade wear during the flood season, which in turn leads to a substantial rise in fatigue damage. When considering wear, the runner blade is considered to have experienced fatigue failure when the maximum amount of fatigue damage is equal to 1. At this point, the life of the runner blade is determined to be approximately 8 years, which aligns with the actual service life of hydro turbines. Therefore, the total fatigue damage at critical points, when accounting for blade wear, is significantly greater than when wear is not considered, which significantly affects the calculation of the blade's fatigue life. Consequently, in basins with high sediment content, the effect of sediment on blade wear should be factored into the fatigue life calculations for hydraulic turbine runners.
## 4 Discussion
Unfortunately, the currently existing macro FE model for a fractured femur fixed with 3 DP implant and locking plate was unable to simulate micro-porous structures at the implant-bone interface and subsequent bone growth due to scale issues. However, an implant surface with 600 \(\upmu\)m porous hole structure can be accurately produced through 3 DP technology (Figure 8). These porous structures can secure the construct stability and provide a good load transfer bonding area, especially in a weight-bearing bone such as the femur. Therefore, the implant-bone interface should easily promote complete bone healing in the presence of these porous structures. In stage 1 the implant stress values are very high and exceed titanium alloy ultimate strength, inducing implant failure/fracture because the bone/implant interface has not been integrated. The highest implant stress value occurred on the outer lattice mesh structure. There is particularly high stress concentration at the mesh grid angles. This phenomenon can be greatly improved by rounding the angles to greatly decrease stress values (Figures 4 and 9). In stage 2 the force can be effectively transmitted from bone to implant after the bone and implant have been integrated and the maximum stress value and system deformation can be greatly reduced. However, the implant stress, screws and proximal interface strain increased slightly after removing the locking plate in stage 3. From this observation, besides the implant the locking plate plays an important role in maintaining the initial construct stability. This also explains why an additional locking plate must be used for this kind of reconstruction surgery. There were some limitations in this study. Materials with linear elastic (homogenous and isotropic) properties were used due to numerical convergence consideration. Only single leg standing was considered as the load condition and the micro-porous structure at the implant-bone interface cannot be simulated to understand micro-implant-bone interface integration using current FE macro modeling. In vitro biomechanical testing was challenging to perform due to the difficulty obtaining patient-specific artificial fracture bone with accurate material properties. Figure 8: The novel patient specific 3 DP titanium implant. Note the central solid cylinder and the outer lattice structure of the implant body, with protected spaces for the morselized bone graft. The perfectly fit bone-implant interface of the implant consists of the proximal shell with a stem and the distal shell, both with unique porous structures facilitating osteointegration.