The present invention relates to Delayed Coking of heavy petroleum residue producing petroleum coke and lighter hydrocarbon products. The invented process utilizes a pre-cracking reactor for mild thermal cracking of the feedstock and intermediate multistage separation system before being subjected to higher severity thermal cracking in delayed coking process, resulting in reduction in overall coke yield.

The present invention relates to Delayed Coking of heavy petroleum residue producing petroleum coke and lighter hydrocarbon products. The invented process utilizes a pre-cracking reactor for mild thermal cracking of the feedstock and intermediate multistage separation system before being subjected to higher severity thermal cracking in delayed coking process, resulting in reduction in overall coke yield.

The present disclosure describes systems, methods, and computer readable media that provide a hybrid approach that uses machine learning techniques and phenomenological reactor models for optimization of steam cracker units. While the phenomenological model allows capturing the physics of a steam cracker using molecular kinetics, the machine learning methods fill the gap between the phenomenological models and more detailed radical kinetics based steam cracker models. Also, machine learning based models can capture actual plant information and provide insight into the variation between the models and plant running conditions. The proposed methodology shows better interpolation and extrapolation capabilities as compared to stand-alone machine learning methods. Also, compared to detailed radical kinetics based models, the approach utilized in embodiments requires much less computational time in order to carry out whole plant-wide optimization or can be used for planning/scheduling purposes.

The present disclosure describes systems, methods, and computer readable media that provide a hybrid approach that uses machine learning techniques and phenomenological reactor models for optimization of steam cracker units. While the phenomenological model allows capturing the physics of a steam cracker using molecular kinetics, the machine learning methods fill the gap between the phenomenological models and more detailed radical kinetics based steam cracker models. Also, machine learning based models can capture actual plant information and provide insight into the variation between the models and plant running conditions. The proposed methodology shows better interpolation and extrapolation capabilities as compared to stand-alone machine learning methods. Also, compared to detailed radical kinetics based models, the approach utilized in embodiments requires much less computational time in order to carry out whole plant-wide optimization or can be used for planning/scheduling purposes.

A substantially linear ceramic or metallic radiant of ellipsoidal or polygonal cross section is placed proximate furnace tubes or coils in the radiant section of a fired heater to increase the radiant heat directed to the surface of the tubes or coils.

A substantially linear ceramic or metallic radiant of ellipsoidal or polygonal cross section is placed proximate furnace tubes or coils in the radiant section of a fired heater to increase the radiant heat directed to the surface of the tubes or coils.

Embodiments disclosed herein relate to systems and processes for producing olefins and/or dienes. The systems and processes may include thermally cracking a C1-C4 hydrocarbon containing feed to produce a cracked hydrocarbon effluent containing a mixture of olefins and paraffins. The systems and processes may also include dehydrogenating the cracked hydrocarbon effluent to produce a dehydrogenated hydrocarbon effluent containing additional olefins and/or dienes.

Embodiments disclosed herein relate to systems and processes for producing olefins and/or dienes. The systems and processes may include thermally cracking a C1-C4 hydrocarbon containing feed to produce a cracked hydrocarbon effluent containing a mixture of olefins and paraffins. The systems and processes may also include dehydrogenating the cracked hydrocarbon effluent to produce a dehydrogenated hydrocarbon effluent containing additional olefins and/or dienes.

The invention relates weldments useful as heat transfer tubes in pyrolysis furnaces. The invention relates to tubes that are useful in pyrolysis furnaces. The weldments include a tubular member and at least one mixing element. The tubular member comprises an aluminum-containing alloy. The mixing element comprises an aluminum-containing alloy. The mixing element's aluminum-containing alloy can be the same as or different from the tubular member's aluminum-containing alloy. Other aspects of the invention relate to pyrolysis furnaces which include such weldments, and the use of such pyrolysis furnaces for hydrocarbon conversion processes such as steam cracking.

The invention relates weldments useful as heat transfer tubes in pyrolysis furnaces. The invention relates to tubes that are useful in pyrolysis furnaces. The weldments include a tubular member and at least one mixing element. The tubular member comprises an aluminum-containing alloy. The mixing element comprises an aluminum-containing alloy. The mixing element's aluminum-containing alloy can be the same as or different from the tubular member's aluminum-containing alloy. Other aspects of the invention relate to pyrolysis furnaces which include such weldments, and the use of such pyrolysis furnaces for hydrocarbon conversion processes such as steam cracking.