dataesr/scientific-paragraphs-categorization huggingface dataset:
B. The Energy Modelling Challenge A fundamental step to enable static energy consumption estimation of embedded software is the ability to accurately characterise and model the energy consumed by the target applications. This requires data collection from each target hardware platform and a model generation methodology. The resulting energy models are directly sourced by static energy analysis tools. Existing techniques may rely on available hardware support or external devices to associate costs with ISA-level constructs. However, these types of models often involve a very deep micro-architectural understanding of the target platform and can require a significant amount of time to develop and validate. Since TeamPlay aims to target multiple different types of architectures, the particular challenge is to develop a configurable modelling methodology that captures platform behaviour at a higher abstraction level while still providing very accurate prediction.
Considering all these non-functional properties at once is, therefore, the main challenge addressed in TeamPlay. WCET analysis is used to determine how much time is spent in the worst case for the execution of a particular piece of software. It is thus a crucial part of the development process of safety-critical embedded systems. Most existing WCET-aware compilation frameworks do not provide a smooth integration of WCET analysis into a compiler  [23] , or do not scale with industrial-grade applications  [24]. Similar considerations apply to the integration of energy consumption and security analysis into compiler infrastructures. In TeamPlay, we targetted full integration and exploitation of ETS analysers at the compilation level, making the use of these tools within each workflow transparent to the developer.
Failure to meet timing constraints could result in a misleading or inconclusive diagnosis; failure to meet the energy budget could deplete the battery before reaching the area of interest. Furthermore, the transmitted images are medical data and hence subject to strict privacy regulations. This requires additional security measures to prevent interception. Technically, the camera pill embeds a single-core Cortex-M0 coupled with a low-power FPGA acting as an image coprocessor. During the lifetime of the project, we successfully applied the full TeamPlay toolchain for predictable architectures (Sec II-A), with the exception of the coordination layer, which could not be used due to a need for hardware-specific optimisations in the scheduler. This processor architecture is fully supported by our static analysis tools, enabling safe and accurate time and energy estimation based on highly accurate energy models  [9].
B. Communication in Space Applications Energy consumption is a major concern in spacecraft, where every little reduction of power consumption that can be achieved without a significant loss of performance is highly valuable. The space-oriented use case includes an image processing and transmission application using SpaceWire  [28]. The proper functioning of the full system is dependent on the timely execution of its software and hardware to avoid missing images. Moreover, the harsh environment requires the overall energy consumed to be minimal. Furthermore, the transmitted images can be of critical sensitivity and must be protected from malicious third-party access. The target hardware device is the LEON3FT-based GR712RC development platform from Cobham-Gaisler  [29]. The runtime environment is provided by a Real-Time Operating System (RTOS) named RTEMS (https://www.
rtems. org/), which executes the image processing and communication program. Due to its predictable-by-design nature, the LEON3FT is fully supported by the TeamPlay toolchain for predictable architectures. The source code has been annotated for all three ETS properties. A complete energy model has been built  [8]  and integrated into the EnergyAnalyser tool that is called by WCC for multi-criteria optimisation. The coordination layer and CSL both gave a green light with a valid schedulability analysis and a certificate proving that the code meets its specified energy and time budget. The Coordination layer also generated the required initialisation, management, and configuration code for the application within the RTEMS runtime ecosystem. Applying the TeamPlay methodology led to an energy improvement of 52% while meeting all deadlines.
Object detection is performed on the payload, and any results are transmitted to the ground station. The proper functioning of the use cases depend on correct soft-timely execution and low energy consumption. Due to overlapping frames, for instance, missing a few deadlines is possible without missing objects, whereas energy constraints are tighter, directly impacting the flight time and thus coverage area  [33]. Three different hardware platforms have been tested: 1) an Apalis TK1; 2) Nvidia TX2; and, 3) Nvidia Nano. In all cases, Linux OS runs use case-specific software, e. g. , C++/CUDA computer vision algorithms for detections on the GPU, and is eventually complemented with Robot Operating System (ROS) middleware  [31] ,  [33]. We applied the TeamPlay toolchain for unpredictable architectures but, as a result of platform complexity, omitted fact checker and SecurityAnalyser, which both require further investigation.
A study of the SAR use case, available in  [34] , exhibits an increment in timing control. Using our TeamPlay methodology, we observe an energy improvement of 18%, resulting in the flight time being increased by approximately 4 minutes. Conversely to the SAR use case, the PA use case  [31] -  [33]  utilized merely energy analysis, yet enabled flight time optimisations. When cruising, the mechanical components of the UAV consumed 28 Watts on average, whereas software components consumed between 2 and 11 Watts, with the toolchain enabling in-flight battery-aware schedulability  [31].
V. CONCLUSION In this paper, we introduced and summarised TeamPlay, a research project funded under the EU Horizon-2020 programme between January 2018 and June 2021. The goal of TeamPlay was to provide the system designer with a working toolchain for developing embedded applications where energy, time and security properties (ETS) are first-class citizens. Our technologies enable developers to target ETS as a design goal of the software, e. g. , to meet time or energy budgets while satisfying security requirements. We considered two architectural classes that we label predictable and complex. In this paper we gave an overview of the TeamPlay methodology for both architecture classes. We further demonstrated our methodology on industrial use cases from a range of domains, namely medical, space, aerial vehicles, and deep learning, where, in some cases, we achieved energy improvements of up to 52%.
In the future, we plan to extend our work in a number of directions. The TeamPlay methodology is currently limited to C and C++ applications for embedded devices; we therefore plan to extend our methodology to cover a much wider range of general-purpose programming languages (such as, e. g. , Java, Python or Haskell), as our proposed methodology is, in principle, generic, and the concepts could be ported to other systems. We further plan to extend our energy-modelling techniques to a wider range of hardware types and to improve our methodology and tool support to design software with ETS properties as a major requirement. Preliminary work has shown that program transformation techniques, such as refactoring tool support, would be very applicable here and thus form a natural extension to our methodology.
Design and safety assessment of fuel pins for application in innovative Generation IV fast reactors calls for a dedicated nuclear fuel modelling and for the extension of the fuel performance code capabilities to the envisaged materials and irradiation conditions. In the INSPYRE Project, comprehensive and physicsbased models for the thermal-mechanical properties of UePu mixed-oxide (MOX) fuels and for fission gas behaviour were developed and implemented in the European fuel performance codes GERMINAL, MACROS and TRANSURANUS. As a follow-up to the assessment of the reference code versions ("pre-INSPYRE", NET 53 (2021) 3367e3378), this work presents the integral validation and benchmark of the code versions extended in INSPYRE ("post-INSPYRE") against two pins from the SUPERFACT-1 fast reactor irradiation experiment.
00), porosity and burn-up were obtained and validated. The assessment included a p-value statistical analysis of the correlation coefficients (on the basis of the experimental dataset fitted), confirming the suitability and representativeness of the models proposed. Thanks to the fitting dataset selected, the correlations cover the values of interest for FR MOX and envisaged for Generation IV applications. In particular, the applicability ranges extend up to high temperatures (2700 K, close to fuel melting, for the thermal conductivity), as well as high Pu contents (50 at. %) and burn-up (12 at. %). These correlations were implemented in the GERMINAL and TRANSURANUS fuel performance codes  [15]  and used in this work to account for the effect of the Am and Np contents of SUPERFACT-1 on the fuel thermal properties.
The correlations developed, based on literature data for fast reactor-type MOX, cover a wide temperature range from room to melting temperature and include the effects of Pu content, fuel stoichiometry, porosity and burn-up (concentrations of fission products)  [20]. These correlations were implemented in the post-INSPYRE versions of the three FPCs involved in INSPYRE  [15]. In addition, the extension of the GERMINAL and TRANSURANUS FPCs included the development of SCIANTIX  [15, 21]  and its coupling with the codes as a module. SCIANTIX is a grain-scale code developed at Politecnico di Milano that models the behaviour of inert gases (fission gases Xe, Kr, as well as helium) by using a cluster dynamics (rate theory) approach  [26] , and solves the physics-based master equations via fast and stable numerical techniques  [27, 28].
The current SCIANTIX modelling enables the treatment of both the intra-granular and inter-granular behaviour of inert gases. It also includes a fuel burn-up module targeting the helium production and allowing the tracking of the fuel composition evolution in terms of the most relevant actinides  [29]. Finally, it describes the formation and gas depletion of the High Burn-up Structure (HBS) at the fuel pellet periphery  [30]. The intra-granular part of the overall model considers single-gas atom diffusion, the three fundamental mechanisms of gas bubble nucleation, re-solution of gas atoms from bubbles and trapping of gas atoms at bubbles, and accounts for the coarsening of intra-granular bubbles along dislocation lines via vacancy inflow  [31]. The inter-granular bubble evolution model currently available in SCIANTIX is the one proposed by Pastore et al.
SCIANTIX was coupled with the GERMINAL and TRANSURANUS fuel performance codes as an inert gas behaviour module. It is called by the FPCs at each point of the adopted fuel radial mesh, in each axial slice discretizing the fuel column. The coupling strategy between the two codes and SCIANTIX, however, differs in some aspects, i. e. , some of the SCIANTIX models were adjusted in GERMINAL by introducing limiting maximum thresholds (e. g. , on the fuel grain growth and on the grain-boundary gas concentration upon saturation)  [15, 41]. The online coupling between TRANS-URANUS and SCIANTIX has been achieved by means of a dedicated Fortran95/Cþþ interface, based on modern Fortran features as interface modules  [15, 42, 43]. The novel, common models (among those described in this Section) implemented in the FPCs and employed in the present work for the simulation (post-INSPYRE) of the SUPERFACT-1 irradiation experiment are summarized in Table  1.
Assessment against experimental data and benchmark of INSPYRE-extended codes This Section presents the assessment of the post-INSPYRE code versions on the available experimental data and the benchmark between the three codes on relevant quantities not measured during the SUPERFACT-1 experimental campaign, in line with the analysis performed in  [14]  using the pre-INSPYRE code versions. The comparison between pre-and post-INSPYRE code results is given for all the results presented below (left and right plots, respectively), to highlight and analyse the differences in the pin performance determined by the novel INSPYRE models implemented in the fuel performance codes.
Validation against integral and local experimental data The most relevant integral code results on the Am-bearing pin SF16  [13, 14]  are collected and compared to the experimental data in Table  2. The values predicted by the pre-INSPYRE code versions, presented in  [14] , are also reported in round brackets. The agreement of the code results with the end-of-life fuel burn-up measured and the amount of fission gas produced is satisfactory, although the burn-up reached at the peak power node is (more) underestimated by post-INSPYRE TRANSURANUS and MACROS, while still overestimated by GERMINAL. The predictions of final fuel burn-up are still within the associated experimental uncertainty, recalling that the experimental value is obtained from the neodymium radial concentration at the end of irradiation, measured by EPMA with an uncertainty of 8%  [22, 23].
e. , that the different models of cladding creep and swelling in the codes have a noticeable impact on the simulation outcomes. This is enhanced by the fuel-cladding gap closure, which is predicted at the axial peak power node by GERMINAL and MACROS (for the Am-pin). The correct simulation of the cladding deformation is challenging since it is the result of the interplay between pellet-cladding interaction, radiation-induced (and potentially thermal) cladding creep and radiation-induced cladding swelling. The radiation-induced components dominate in the correlations applied in the codes and lead to an underestimation of the impact of the local temperature on the cladding profilometry. The remarkable agreement of the GERMINAL results with the data shows the importance of equipping the codes with a refined cladding swelling model based on a large experimental database, as that available in GERMINAL for 15-15Ti claddings  [7, 14].
Since the cladding modelling was not a focus of the INSPYRE Project, the discrepancies identified in the pre-INSPYRE code versions  [14]  remain in the post-INSPYRE versions. V ¼ ÀDV V ig þ ÀDV V gf ¼ 4 3 pN ig R 3 ig þ 3 a 4p 3 N gf R The comparison of the pre-and post-INSPYRE versions of the MACROS code allows identifying the separate impact of the novel models for the fuel mechanical properties, i. e. , the MOX Young's modulus and thermal expansion (since these are the only INSPYRE modelling advancements introduced in MACROS)  [20]. In particular, the wider gap size evolving in time yielded by post-INSPYRE MACROS (from a lower fuel thermal expansion predicted) suggests a milder mechanical interaction between fuel and cladding, occurring just during the last irradiation cycle. This contributes to the lower radial deformation of the cladding at the end of life compared to the pre-INSPYRE result (Fig.
The trends yielded by the codes are all mainly determined by the axial pin power distribution, i. e. , they exhibit peaks in both the fuel central void and the columnar grain size around the axial peak power node. Compared to the pre-INSPYRE results  [14] , the post-INSPYRE code results correspond to generally lower fuel restructuring, consistently with the lower fuel central temperature regimes at beginning of irradiation (see Fig. 5 ), in particular in the TRANSURANUS case. This leads to an underestimation of the experimental fuel central void by TRANSURANUS, while the pre-INSPYRE results were in excellent agreement with the measurements available, as shown in Fig. 2   properties have been adopted in MACROS, Section 2) and still the most accurate with respect to the experimental data. The post-INSPYRE models, however, allow for a homogenization of the code results.
This represents a remarkable proof of the importance and effectiveness of informing engineering-level FPCs with a physics-based modelling of lower-length scale processes, as achieved during INSPYRE via the coupling of FPCs with the SCIANTIX module for fission gas behaviour. The evolution according to post-INSPYRE MACROS resembles the pre-INSPYRE one, which could be expected since MACROS was not coupled with the SCIANTIX models. The FGR in the fuel-cladding gap has a thermal feedback (via the gap conductance) on the fuel temperature regime predicted by post-INSPYRE codes (Fig. 5 ), especially GERMINAL and TRANS-URANUS which benefited from the coupling with SCIANTIX. The gap conductance is also determined by the residual width of the fuel-cladding gap. GERMINAL predicts a fast gap closure during the first irradiation cycle and a gap continuously closed until the end of irradiation for both the Am-and Np-bearing pins, in line with the pre-INSPYRE result presented in  [14].
4 ), fission gases and fission products (presented for the pre-INSPYRE codes in  [14] ), however, still exhibit accuracy gaps. Hence, the comparison of the pin performance results obtained from the post-INSPYRE code versions with both the pre-INSPYRE ones  [14]  and the experimental data allows the identification of various improvement paths. First, the current GERMINAL//SCIANTIX and TRANSURANUS// SCIANTIX coupled suites  [15]  are open to further adaptations and developments tackling FR irradiation conditions. Among the improvements needed, a proper modelling of the normal growth of FR fuel grains seems dominant, currently limited in GERMINAL while switched off in TRANSURANUS for FR irradiation conditions  [15, 41]  (since the model currently available in the code is tailored for thermal -light water -conditions  [50] ).
g. ,  [53] ). Efforts along these directions are ongoing for the TRANSURANUS code, to obtain a TRANSURANUS// SCIANTIX coupled suite covering a wide set of physical aspects affecting the behaviour of mixed UePu oxide fuels under FR irradiation conditions. For what concerns the radial concentration profiles of actinides at the end of life (e. g. , Pu, Fig. 4 ), the results obtained from post-INSPYRE codes highlight the need to acquire more reliable mobility data for the GERMINAL and TRANSURANUS codes, and the implementation of a redistribution module for the MACROS code. Recent results on plutonium self-diffusion have been obtained in the framework of INSPYRE and presented in  [54, 55] , and the consideration of these data for future versions of the GERMINAL and TRANSURANUS codes is planned.
Other code improvements recognized from the present work concern the modelling of the fuel-cladding gap dynamics, which impacts significantly (together with the fuel thermal conductivity) the fuel temperature profile and its evolution during irradiation. Modelling discrepancies concern the way different codes (GERMINAL and TRANSURANUS especially) treat fuel radial relocation, both regarding the fuel displacement before gap closure and the relocation accommodation after gap closure. GERMINAL accounts for a complete accommodation of cracks opened by fuel relocation after the gap closure  [7] , which is in line with a model implemented in the recent FUTURE code targeting the design of an ADS in China  [56] , while TRANSURANUS currently does not allow any relocation recovery, neither in the axial nor in the radial direction.
Developments are ongoing to include in TRANSURANUS the modelling of a partial recovery of fuel fragments based on an empirical modelling approach  [57]. Then, as pointed out by the strongly different gap evolutions (and consequently, different gap heat transfer), the modelling of gap conductance in the codes, currently accounting in different ways for gap closure and fuelcladding mechanical interaction  [7, 58] , would benefit from additional accurate separate-effect measurements, especially for beginning-of-life conditions. A deeper analysis of the various gap conductance models currently applied could also contribute to further reduce the spread in the predicted fuel central temperatures at the beginning of irradiation (Fig. 5 ). In addition, at high fuel burn-up, the code comparison pointed out the need to implement a model accounting for the JOG (Joint Oxide-Gaine) [59e61] formation and evolution in TRANSURANUS and MACROS, which is instead already modelled in GERMINAL  [7].
Summary and conclusions We have presented in this paper an integral assessment and benchmark of the latest versions of the GERMINAL, MACROS and TRANSURANUS fuel performance codes, equipped with models developed in the INSPYRE H2020 European Project, addressing the thermal-mechanical properties and fission gas-related phenomena of MOX fuels under irradiation in FR conditions. This work is the second step after the first assessment  [14]  of the codes' capabilities prior to the INSPYRE developments ("pre-INSPYRE"). The modelling advancements implemented in the "post-INSPYRE" code versions concern the MOX thermal conductivity and melting temperature, thermal expansion and Young's modulus, and the physics-based treatment of fission gas behaviour (intra-and intergranular dynamics) and release, by means of the coupling of FPCs with the SCIANTIX meso-scale tool.
The result is both a quantitative agreement with the reconstructed/experimental data on fission gas production and release and an alignment of the predictions from different FPCs. This achievement stresses the importance of including in fuel performance codes mechanistic models for as many material properties and pin phenomena as possible. SCIANTIX offers a multi-scale approach and environment designed to be easily extended and tailored by means of the model parameters or by considering additional gas-related mechanisms. Moreover, the combination of code developments and benchmarking performed in the INSPYRE Project has allowed identifying relevant gaps towards the reliable application of simulation tools to the fuel pin performance under FR irradiation conditions. The SUPERFACT-1 pins considered are representative of Generation IV FR designs in terms of fuel composition (including minor actinides for transmutation purposes), cladding material (15-15Ti stainless steel) and irradiation conditions (i.
The three-dimensional distribution of the Ly forest has been extensively used to constrain cosmology through measurements of the baryon acoustic oscillations (BAO) scale. However, more cosmological information could be extracted from the full shapes of the Ly forest correlations through the Alcock-Paczyński (AP) effect. In this work, we prepare for a cosmological analysis of the full shape of the Ly forest correlations by studying synthetic data of the extended Baryon Oscillation Spectroscopic Survey (eBOSS). We use a set of one hundred eBOSS synthetic data sets in order to validate such an analysis. These mocks undergo the same analysis process as the real data. We perform a full-shape analysis on the mean of the correlation functions measured from the one hundred eBOSS realizations, and find that our model of the Ly correlations performs well on current data sets.
2021). Cuceu et al. (2021)  did show that it is possible to measure the growth rate from the quasar RSD parameter in a joint analysis of the Ly auto-correlation and its cross-correlation with quasars. However, this would not be a significant measurement with eBOSS. Therefore, in this work we only focus on the AP information, and leave RSD measurements for future work using larger surveys such as the Dark Energy Spectroscopic Instrument  (DESI Collaboration et al. 2016). Our objective in this work is to analyse the full shape of the Ly forest correlation functions in simulated data in order to understand how well current models perform relative to the expected precision of the eBOSS DR16 data. This analysis is meant as a first step towards a full-shape analysis of the eBOSS Ly 3D correlation functions.