Geothermal power plants with maximized specific power output : optimal working fluid and operating conditions of subcritical and transcritical organic rankine cycles

In this paper, the design of an Organic Rankine Cycle (ORC) is optimized by means of numerical simulations. The systems of interest are the subcritical and transcritical thermodynamic cycles. Optimizations are performed with the objective of determining the design that maximizes the specific power output. The design variables include the operating parameters (pressures, mass flow rates), and the best working fluid is determined by comparing the performance of 36 refrigerants. Optimization runs are performed for a wide range of geofluid temperatures (from 80 to 180 °C), and for a wide range of condenser temperature (from 0.1 to 50 °C). The results are summarized in charts that may be used as efficient tools for designing optimal geothermal power plants. Finally, an approximate analysis allowed to develop a new correlation for predicting the maximal specific power output of an ORC

Maximizing specific work output extracted from engine exhaust with novel inverted Brayton cycles over a large range of operating conditions

The heat contained in internal combustion engine exhaust gases can be converted into mechanical energy by using an Inverted Brayton Cycle (IBC). In this paper, five different IBC versions are numerically modeled and optimized to maximize their specific work output: (i) basic IBC, (ii) IBC with liquid water drainage (IBC/D), (iii) IBC with liquid water drainage and a steam turbine (IBC/D/S), (iv) IBC with liquid water drainage and a refrigeration cycle (IBC/D/R), and (v) IBC with liquid water drainage, a steam turbine and a refrigeration cycle (IBC/D/S/R). The three latter cycles are presented for the first time in literature. The optimization is performed for a wide range of inlet gases temperatures (600–1200 K) and heat sink temperatures (280–340 K). Among the five IBCs, the IBC/D/S/R has the highest specific work output for the whole range of operating temperatures. A comparison with the subcritical Rankine cycle and Organic Rankine Cycles using isobutane and benzene shows that an IBC system might be a better choice for specific operating temperatures. Liquid water addition in the IBC/D/S/R leads to optimized designs using only the steam turbine at high inlet gas temperatures, indicating that a Rankine cycle is better suited for these conditions

Maximizing specific work output extracted from engine exhaust with novel inverted Brayton cycles over a large range of operating conditions

The heat contained in internal combustion engine exhaust gases can be converted into mechanical energy by using an Inverted Brayton Cycle (IBC). In this paper, five different IBC versions are numerically modeled and optimized to maximize their specific work output: (i) basic IBC, (ii) IBC with liquid water drainage (IBC/D), (iii) IBC with liquid water drainage and a steam turbine (IBC/D/S), (iv) IBC with liquid water drainage and a refrigeration cycle (IBC/D/R), and (v) IBC with liquid water drainage, a steam turbine and a refrigeration cycle (IBC/D/S/R). The three latter cycles are presented for the first time in literature. The optimization is performed for a wide range of inlet gases temperatures (600–1200 K) and heat sink temperatures (280–340 K). Among the five IBCs, the IBC/D/S/R has the highest specific work output for the whole range of operating temperatures. A comparison with the subcritical Rankine cycle and Organic Rankine Cycles using isobutane and benzene shows that an IBC system might be a better choice for specific operating temperatures. Liquid water addition in the IBC/D/S/R leads to optimized designs using only the steam turbine at high inlet gas temperatures, indicating that a Rankine cycle is better suited for these conditions

Experimental Investigation of Deep Learning for Digital Signal Processing in Short Reach Optical Fiber Communications

We investigate methods for experimental performance enhancement of auto-encoders based on a recurrent neural network (RNN) for communication over dispersive nonlinear channels. In particular, our focus is on the recently proposed sliding window bidirectional RNN (SBRNN) optical fiber autoencoder. We show that adjusting the processing window in the sequence estimation algorithm at the receiver improves the reach of simple systems trained on a channel model and applied "as is" to the transmission link. Moreover, the collected experimental data was used to optimize the receiver neural network parameters, allowing to transmit 42 Gb/s with bit-error rate (BER) below the 6.7% hard-decision forward error correction threshold at distances up to 70km as well as 84 Gb/s at 20 km. The investigation of digital signal processing (DSP) optimized on experimental data is extended to pulse amplitude modulation with receivers performing sliding window sequence estimation using a feed-forward or a recurrent neural network as well as classical nonlinear Volterra equalization. Our results show that, for fixed algorithm memory, the DSP based on deep learning achieves an improved BER performance, allowing to increase the reach of the system.Comment: Invited paper at the IEEE International Workshop on Signal Processing Systems (SiPS) 202

End-to-end Deep Learning of Optical Fiber Communications

In this paper, we implement an optical fiber communication system as an end-to-end deep neural network, including the complete chain of transmitter, channel model, and receiver. This approach enables the optimization of the transceiver in a single end-to-end process. We illustrate the benefits of this method by applying it to intensity modulation/direct detection (IM/DD) systems and show that we can achieve bit error rates below the 6.7\% hard-decision forward error correction (HD-FEC) threshold. We model all componentry of the transmitter and receiver, as well as the fiber channel, and apply deep learning to find transmitter and receiver configurations minimizing the symbol error rate. We propose and verify in simulations a training method that yields robust and flexible transceivers that allow---without reconfiguration---reliable transmission over a large range of link dispersions. The results from end-to-end deep learning are successfully verified for the first time in an experiment. In particular, we achieve information rates of 42\,Gb/s below the HD-FEC threshold at distances beyond 40\,km. We find that our results outperform conventional IM/DD solutions based on 2 and 4 level pulse amplitude modulation (PAM2/PAM4) with feedforward equalization (FFE) at the receiver. Our study is the first step towards end-to-end deep learning-based optimization of optical fiber communication systems.Comment: submitted to IEEE/OSA Journal of Lightwave Technolog

Experimental parametric study of 128 Gb/s PAM-4 transmission system using a multi-electrode silicon photonic Mach Zehnder modulator

We present an experimental study and analysis of a travelling wave series push-pull silicon photonic multi-electrode Mach-Zehnder modulator (ME-MZM) and compare its performance with a single-electrode travelling wave Mach-Zehnder modulator (TWMZM). Utilizing the functionality of the ME-MZM structure plus digital-signal-processing, we report: 1) the C-band transmission of 84 Gb/s OOK modulated data below the KP4 forward error correction threshold with 2 Vpp drive voltage over a distance of 2 km; 2) the transmission of a 128 Gb/s optical 4-level pulse amplitude modulated signal over 1 km of fiber; and 3) the generation of a 168 Gb/s PAM-4 signal using two electrical OOK signals. By comparing the transmission system performance measurements for the ME-MZM with measurements performed using a similar series push-pull TWMZM, we show that the ME-MZM provides a clear advantage in achieving higher baud PAM-4 generation and transmission compared to a TWMZM

Silicon photonic mach-zehnder modulator architectures for on chip PAM-4 signal generation and transmission

Four level pulse amplitude modulation (PAM-4) has become the modulation format of choice to replace on-off keying (OOK) for the 400 Gb/s short reach optical communications systems. In this manuscript, we investigate the possible modifications to conventional Mach-Zehnder modulator structures to improve the system performance. We present 3 different Silicon photonic Mach-Zehnder modulator architectures for generating PAM-4 in the optical domain using OOK electrical driving signals. We investigate the transfer function and linearity of each modulator, and experimentally compare their PAM-4 generation and transmission performance with and without use of digital signal processing (DSP). We achieve the highest reported PAM-4 generation and transmission without the use of DSP. The power consumption of each modulator is presented, and we experimentally show that multi-electrode Mach-Zehnder modulators provide a clear advantage at higher symbol rates compared to conventional Mach-Zehnder modulators

Digital signal processing assessment for optical coherent receiver using dual-polarization Quadrature phase shift keying modulation

In this work, we evaluate different approaches of digital signal processing applied after a coherent receiver in order to recover the binary information of an optical signal modulated in Dual-Polarization Quadrature Phase Shift Keying. We explain in details the functioning of a coherent receiver as well as the optical and electrical signals travelling inside. We present the criteria of the two lasers employed for modulation and demodulation, i.e., the signal and local oscillator lasers, as a function of the modulation format and the binary rate. We expose all the required signal processing for information recovery out of a coherent receiver and mention those who will be assessed in this work, along with the reason of their selection. Subsequently, the metric to assess the different methods is introduced. The latter is twofold and consists of the computational complexity and the final bit error rate that each approach yields. The schematics of the test bed follows in parallel with the parameter space of our setup. The computational complexity and the bit error rate of ten different approaches are presented, and an optimal configuration of methods and parameters to use for such modulation and receiver is deduced.Dans ce travail, nous évaluons différentes approches de traitement de signaux numériques pour un récepteur cohérent optique dans le but de recouvrir l'information binaire d'un signal modulé sur double polarization et quatre niveaux de phase, ou « Dual-Polarization QPSK ». Nous expliquons en détail le fonctionnement d'un récepteur cohérent ainsi que les signaux optiques et électriques qui s'y propagent. Nous présentons les critères des deux lasers utilisés pour la modulation et la démodulation cohérente, i.e., les lasers signal et oscillateur local, en fonction du format de modulation utilisé et du taux binaire. Nous exposons tous les traitements de signaux numériques requis pour recouvrir l'information sortant d'un récepteur cohérent et mentionnons ceux qui seront évalués dans ce travail ainsi que les raisons de leur sélection. Par la suite, nous introduisons la métrique d'évaluation des différentes approches. Cette dernière comporte deux facettes, soit la complexité de calcul des différents algorithmes et paramètres utilisés ainsi que le taux d'erreur binaire final que l'ensemble des processus produisent lorsqu'une certaine approche est employée. La présentation schématique du banc de test suit de concert avec l'espace des paramètres du montage. La complexité de calcul et le taux d'erreur binaire de dix différentes approches sont présentés et une configuration optimale des paramètres et méthodes pour un tel format de modulation et receveur est déduite